NLP_C3W1_Practice_Assignment.ipynb

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    "# Assignment 1:  Sentiment with Deep Neural Networks\n",
    "\n",
    "Welcome to the first assignment of course 3. **This is a practice assignment**, which means that the grade you receive won't count towards your final grade of the course. **However you can still submit your solutions and receive a grade along with feedback from the grader.** Before getting started take some time to read the following tips: \n",
    "\n",
    "#### TIPS FOR SUCCESSFUL GRADING OF YOUR ASSIGNMENT:\n",
    "\n",
    "- All cells are frozen except for the ones where you need to submit your solutions.\n",
    "\n",
    "- You can add new cells to experiment but these will be omitted by the grader, so don't rely on newly created cells to host your solution code, use the provided places for this.\n",
    "\n",
    "- You can add the comment # grade-up-to-here in any graded cell to signal the grader that it must only evaluate up to that point. This is helpful if you want to check if you are on the right track even if you are not done with the whole assignment. Be sure to remember to delete the comment afterwards!\n",
    "\n",
    "- To submit your notebook, save it and then click on the blue submit button at the beginning of the page.\n",
    "\n",
    "\n",
    "In this assignment, you will explore sentiment analysis using deep neural networks. "
   ]
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    "## Table of Contents\n",
    "- [1 - Import the Libraries](#1)\n",
    "- [2 - Importing the Data](#2)\n",
    "    - [2.1 - Load and split the Data](#2-1)\n",
    "    - [2.2 - Build the Vocabulary](#2-2)\n",
    "        - [Exercise 1 - build_vocabulary](#ex-1)\n",
    "    - [2.3 - Convert a Tweet to a Tensor](#2-3)\n",
    "        - [Exercise 2 - max_len](#ex-2)\n",
    "        - [Exercise 3 - padded_sequences](#ex-3)\n",
    "- [3 - Define the structure of the neural network layers](#3)\n",
    "    - [3.1 - ReLU](#3-1)\n",
    "        - [Exercise 4 - relu](#ex-4)\n",
    "    - [3.2 - Sigmoid](#3.2)\n",
    "        - [Exercise 5 - sigmoid](#ex-5)\n",
    "    - [3.3 - Dense class](#3-3)\n",
    "        - [Exercise 6 - Dense](#ex-6)\n",
    "    - [3.3 - Model](#3-4)\n",
    "        - [Exercise 7 - create_model](#ex-7)\n",
    "- [4 - Evaluate the model](#4)\n",
    "    - [4.1 Predict on Data](#4-1)\n",
    "- [5 - Test With Your Own Input](#5)\n",
    "    - [5.1 Create the Prediction Function](#5-1)\n",
    "        - [Exercise 8 - graded_very_positive_tweet](#ex-8)\n",
    "- [6 - Word Embeddings](#6)"
   ]
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    "In course 1, you implemented Logistic regression and Naive Bayes for sentiment analysis. Even though the two models performed very well on the dataset of tweets, they fail to catch any meaning beyond the meaning of words. For this you can use neural networks. In this assignment, you will write a program that uses a simple deep neural network to identify sentiment in text. By completing this assignment, you will: \n",
    "\n",
    "- Understand how you can design a neural network using tensorflow\n",
    "- Build and train a model\n",
    "- Use a binary cross-entropy loss function\n",
    "- Compute the accuracy of your model\n",
    "- Predict using your own input\n",
    "\n",
    "As you can tell, this model follows a similar structure to the one you previously implemented in the second course of this specialization. \n",
    "- Indeed most of the deep nets you will be implementing will have a similar structure. The only thing that changes is the model architecture, the inputs, and the outputs. In this assignment, you will first create the neural network layers from scratch using `numpy` to better understand what is going on. After this you will use the library `tensorflow` for building and training the model."
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    "<a name=\"1\"></a>\n",
    "## 1 - Import the Libraries\n",
    "\n",
    "Run the next cell to import the Python packages you'll need for this assignment.\n",
    "\n",
    "Note the `from utils import ...` line. This line imports the functions that were specifically written for this assignment. If you want to look at what these functions are, go to `File -> Open...` and open the `utils.py` file to have a look."
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     "text": [
      "[nltk_data] Downloading package twitter_samples to\n",
      "[nltk_data]     /usr/local/share/nltk_data...\n",
      "[nltk_data]   Package twitter_samples is already up-to-date!\n",
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /usr/local/share/nltk_data...\n",
      "[nltk_data]   Unzipping corpora/stopwords.zip.\n",
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     /usr/local/share/nltk_data...\n",
      "[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     /usr/local/share/nltk_data...\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n",
    "\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "from utils import load_tweets, process_tweet\n",
    "\n",
    "%matplotlib inline"
   ]
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   "source": [
    "import w1_unittest"
   ]
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    "<a name=\"2\"></a>\n",
    "## 2 - Import the Data\n",
    "\n",
    "<a name=\"2-1\"></a>\n",
    "### 2.1 - Load and split the Data\n",
    "\n",
    "- Import the positive and negative tweets\n",
    "- Have a look at some examples of the tweets\n",
    "- Split the data into the training and validation sets\n",
    "- Create labels for the data"
   ]
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     "text": [
      "The number of positive tweets: 5000\n",
      "The number of negative tweets: 5000\n"
     ]
    }
   ],
   "source": [
    "# Load positive and negative tweets\n",
    "all_positive_tweets, all_negative_tweets = load_tweets()\n",
    "\n",
    "# View the total number of positive and negative tweets.\n",
    "print(f\"The number of positive tweets: {len(all_positive_tweets)}\")\n",
    "print(f\"The number of negative tweets: {len(all_negative_tweets)}\")"
   ]
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  {
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   "source": [
    "Now you can have a look at some examples of tweets. "
   ]
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     "text": [
      "Positive tweet example:\n",
      "yeaaaah yippppy!!!  my accnt verified rqst has succeed got a blue tick mark on my fb profile :) in 15 days\n",
      "\n",
      "Negative tweet example:\n",
      "Dang starting next week I have \"work\" :(\n"
     ]
    }
   ],
   "source": [
    "# Change the tweet number to any number between 0 and 4999 to see a different pair of tweets.\n",
    "tweet_number = 4\n",
    "print('Positive tweet example:')\n",
    "print(all_positive_tweets[tweet_number])\n",
    "print('\\nNegative tweet example:')\n",
    "print(all_negative_tweets[tweet_number])"
   ]
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    "Here you will process the tweets. This part of the code has been implemented for you.  The processing includes:\n",
    "\n",
    "- tokenizing the sentence (splitting to words)\n",
    "- removing stock market tickers like $GE\n",
    "- removing old style retweet text \"RT\"\n",
    "- removing hyperlinks\n",
    "- removing hashtags\n",
    "- lowercasing\n",
    "- removing stopwords and punctuation\n",
    "- stemming\n",
    "\n",
    "Some of these things are general steps you would do when processing any text, some others are very \"tweet-specific\". The details of the process_tweet function are available in utils.py file"
   ]
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    "# Process all the tweets: tokenize the string, remove tickers, handles, punctuation and stopwords, stem the words\n",
    "all_positive_tweets_processed = [process_tweet(tweet) for tweet in all_positive_tweets]\n",
    "all_negative_tweets_processed = [process_tweet(tweet) for tweet in all_negative_tweets]"
   ]
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  {
   "cell_type": "markdown",
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   "source": [
    "Now you can have a look at some examples of how the tweets look like after being processed."
   ]
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     "text": [
      "Positive processed tweet example:\n",
      "['yeaaah', 'yipppy', 'accnt', 'verify', 'rqst', 'succeed', 'get', 'blue', 'tick', 'mark', 'fb', 'profile', ':)', '15', 'day']\n",
      "\n",
      "Negative processed tweet example:\n",
      "['dang', 'start', 'next', 'week', 'work', ':(']\n"
     ]
    }
   ],
   "source": [
    "# Change the tweet number to any number between 0 and 4999 to see a different pair of tweets.\n",
    "tweet_number = 4\n",
    "print('Positive processed tweet example:')\n",
    "print(all_positive_tweets_processed[tweet_number])\n",
    "print('\\nNegative processed tweet example:')\n",
    "print(all_negative_tweets_processed[tweet_number])"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Next, you split the tweets into the training and validation datasets. For this example you can use 80 % of the data for training and 20 % of the data for validation."
   ]
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     "text": [
      "There are 8000 sentences for training.\n",
      "There are 8000 labels for training.\n",
      "\n",
      "There are 2000 sentences for validation.\n",
      "There are 2000 labels for validation.\n"
     ]
    }
   ],
   "source": [
    "# Split positive set into validation and training\n",
    "val_pos = all_positive_tweets_processed[4000:]\n",
    "train_pos = all_positive_tweets_processed[:4000]\n",
    "# Split negative set into validation and training\n",
    "val_neg = all_negative_tweets_processed[4000:]\n",
    "train_neg = all_negative_tweets_processed[:4000]\n",
    "\n",
    "train_x = train_pos + train_neg \n",
    "val_x  = val_pos + val_neg\n",
    "\n",
    "# Set the labels for the training and validation set (1 for positive, 0 for negative)\n",
    "train_y = [[1] for _ in train_pos] + [[0] for _ in train_neg]\n",
    "val_y  = [[1] for _ in val_pos] + [[0] for _ in val_neg]\n",
    "\n",
    "print(f\"There are {len(train_x)} sentences for training.\")\n",
    "print(f\"There are {len(train_y)} labels for training.\\n\")\n",
    "print(f\"There are {len(val_x)} sentences for validation.\")\n",
    "print(f\"There are {len(val_y)} labels for validation.\")"
   ]
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   "source": [
    "<a name=\"2-2\"></a>\n",
    "### 2.2 - Build the Vocabulary\n",
    "\n",
    "Now build the vocabulary.\n",
    "- Map each word in each tweet to an integer (an \"index\"). \n",
    "- Note that you will build the vocabulary based on the training data. \n",
    "- To do so, you will assign an index to every word by iterating over your training set.\n",
    "\n",
    "The vocabulary will also include some special tokens\n",
    "- `''`: padding\n",
    "- `'[UNK]'`: a token representing any word that is not in the vocabulary."
   ]
  },
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   "source": [
    "<a name=\"ex-1\"></a>\n",
    "### Exercise 1 - build_vocabulary\n",
    "Build the vocabulary from all of the tweets in the training set."
   ]
  },
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     "text": [
      "Vocabulary contains 9535 words\n",
      "\n",
      "{'': 0, '[UNK]': 1, 'followfriday': 2, 'top': 3, 'engage': 4, 'member': 5, 'community': 6, 'week': 7, ':)': 8, 'hey': 9, 'james': 10, 'odd': 11, ':/': 12, 'please': 13, 'call': 14, 'contact': 15, 'centre': 16, '02392441234': 17, 'able': 18, 'assist': 19, 'many': 20, 'thanks': 21, 'listen': 22, 'last': 23, 'night': 24, 'bleed': 25, 'amazing': 26, 'track': 27, 'scotland': 28, 'congrats': 29, 'yeaaah': 30, 'yipppy': 31, 'accnt': 32, 'verify': 33, 'rqst': 34, 'succeed': 35, 'get': 36, 'blue': 37, 'tick': 38, 'mark': 39, 'fb': 40, 'profile': 41, '15': 42, 'day': 43, 'one': 44, 'irresistible': 45, 'flipkartfashionfriday': 46, 'like': 47, 'keep': 48, 'lovely': 49, 'customer': 50, 'wait': 51, 'long': 52, 'hope': 53, 'enjoy': 54, 'happy': 55, 'friday': 56, 'lwwf': 57, 'second': 58, 'thought': 59, '’': 60, 'enough': 61, 'time': 62, 'dd': 63, 'new': 64, 'short': 65, 'enter': 66, 'system': 67, 'sheep': 68, 'must': 69, 'buy': 70, 'jgh': 71, 'go': 72, 'bayan': 73, ':D': 74, 'bye': 75, 'act': 76, 'mischievousness': 77, 'etl': 78, 'layer': 79, 'in-house': 80, 'warehouse': 81, 'app': 82, 'katamari': 83, 'well': 84, '…': 85, 'name': 86, 'imply': 87, ':p': 88, 'influencers': 89, 'love': 90, 'big': 91, '...': 92, 'juicy': 93, 'selfies': 94, 'follow': 95, 'perfect': 96, 'already': 97, 'know': 98, \"what's\": 99, 'great': 100, 'opportunity': 101, 'junior': 102, 'triathletes': 103, 'age': 104, '12': 105, '13': 106, 'gatorade': 107, 'series': 108, 'entry': 109, 'lay': 110, 'greeting': 111, 'card': 112, 'range': 113, 'print': 114, 'today': 115, 'job': 116, ':-)': 117, \"friend's\": 118, 'lunch': 119, 'yummm': 120, 'nostalgia': 121, 'tb': 122, 'ku': 123, 'id': 124, 'conflict': 125, 'help': 126, \"here's\": 127, 'screenshot': 128, 'work': 129, 'hi': 130, 'liv': 131, 'hello': 132, 'need': 133, 'something': 134, 'u': 135, 'fm': 136, 'twitter': 137, '—': 138, 'sure': 139, 'thing': 140, 'dm': 141, 'x': 142, 'follower': 143, \"i've\": 144, 'hear': 145, 'four': 146, 'season': 147, 'pretty': 148, 'dope': 149, 'penthouse': 150, 'obvs': 151, 'gobigorgohome': 152, 'fun': 153, \"y'all\": 154, 'yeah': 155, 'suppose': 156, 'lol': 157, 'chat': 158, 'bit': 159, 'youth': 160, '💅🏽': 161, '💋': 162, 'see': 163, 'year': 164, 'thank': 165, 'rest': 166, 'quickly': 167, 'bed': 168, 'music': 169, 'fix': 170, 'dream': 171, 'spiritual': 172, 'ritual': 173, 'festival': 174, 'népal': 175, 'beginning': 176, 'line-up': 177, 'leave': 178, 'sarah': 179, 'send': 180, 'email': 181, 'bitsy@bitdefender.com': 182, \"we'll\": 183, 'asap': 184, 'lols': 185, 'kik': 186, 'hatessuce': 187, '32429': 188, 'kikme': 189, 'lgbt': 190, 'tinder': 191, 'nsfw': 192, 'akua': 193, 'cumshot': 194, 'come': 195, 'house': 196, 'nsn_supplements': 197, 'effective': 198, 'press': 199, 'release': 200, 'distribution': 201, 'result': 202, 'link': 203, 'remove': 204, 'pressrelease': 205, 'newsdistribution': 206, 'bam': 207, 'bestfriend': 208, 'lot': 209, 'warsaw': 210, '<3': 211, 'x46': 212, 'everyone': 213, 'watch': 214, 'documentary': 215, 'earthling': 216, 'youtube': 217, 'support': 218, 'buuut': 219, 'oh': 220, 'look': 221, 'forward': 222, 'visit': 223, 'next': 224, 'letsgetmessy': 225, 'jo': 226, 'make': 227, 'feel': 228, 'never': 229, 'anyone': 230, 'kpop': 231, 'flesh': 232, 'good': 233, 'girl': 234, 'best': 235, 'wish': 236, 'reason': 237, 'epic': 238, 'soundtrack': 239, 'shout': 240, 'add': 241, 'video': 242, 'playlist': 243, 'would': 244, 'dear': 245, 'jordan': 246, 'okay': 247, 'fake': 248, 'gameplays': 249, ';)': 250, 'haha': 251, 'im': 252, 'kidding': 253, 'stuff': 254, 'exactly': 255, 'product': 256, 'line': 257, 'etsy': 258, 'shop': 259, 'check': 260, 'vacation': 261, 'rechargeable': 262, 'normally': 263, 'charger': 264, 'asleep': 265, 'talk': 266, 'sooo': 267, 'someone': 268, 'text': 269, 'yes': 270, 'bet': 271, \"he'll\": 272, 'fit': 273, 'speech': 274, 'pity': 275, 'green': 276, 'garden': 277, 'midnight': 278, 'sun': 279, 'beautiful': 280, 'canal': 281, 'dasvidaniya': 282, 'till': 283, 'scout': 284, 'sg': 285, 'future': 286, 'wlan': 287, 'pro': 288, 'conference': 289, 'asia': 290, 'change': 291, 'lollipop': 292, '🍭': 293, 'nez': 294, 'agnezmo': 295, 'oley': 296, 'mama': 297, 'stand': 298, 'strong': 299, 'god': 300, 'misty': 301, 'baby': 302, 'cute': 303, 'woohoo': 304, \"can't\": 305, 'sign': 306, 'yet': 307, 'still': 308, 'think': 309, 'mka': 310, 'liam': 311, 'access': 312, 'welcome': 313, 'stats': 314, 'arrive': 315, '1': 316, 'unfollowers': 317, 'via': 318, 'surprise': 319, 'figure': 320, 'happybirthdayemilybett': 321, 'sweet': 322, 'talented': 323, 'amaze': 324, '2': 325, 'plan': 326, 'drain': 327, 'gotta': 328, 'timezones': 329, 'parent': 330, 'proud': 331, 'least': 332, 'maybe': 333, 'sometimes': 334, 'grade': 335, 'al': 336, 'grande': 337, 'manila_bro': 338, 'choose': 339, 'let': 340, 'around': 341, '..': 342, 'side': 343, 'world': 344, 'eh': 345, 'take': 346, 'care': 347, 'finally': 348, 'fuck': 349, 'weekend': 350, 'real': 351, 'x45': 352, 'join': 353, 'hushedcallwithfraydoe': 354, 'gift': 355, 'yeahhh': 356, 'hushedpinwithsammy': 357, 'event': 358, 'might': 359, 'luv': 360, 'really': 361, 'appreciate': 362, 'share': 363, 'wow': 364, 'tom': 365, 'gym': 366, 'monday': 367, 'invite': 368, 'scope': 369, 'influencer': 370, 'friend': 371, 'nude': 372, 'sleep': 373, 'birthday': 374, 'want': 375, 't-shirt': 376, 'cool': 377, 'haw': 378, 'phela': 379, 'mom': 380, 'obviously': 381, 'prince': 382, 'charm': 383, 'stage': 384, 'luck': 385, 'tyler': 386, 'hipster': 387, 'glass': 388, 'marty': 389, 'glad': 390, 'do': 391, 'afternoon': 392, 'read': 393, 'kahfi': 394, 'finish': 395, 'ohmyg': 396, 'yaya': 397, 'dub': 398, 'stalk': 399, 'ig': 400, 'gondooo': 401, 'moo': 402, 'tologooo': 403, 'become': 404, 'detail': 405, 'zzz': 406, 'xx': 407, 'physiotherapy': 408, 'hashtag': 409, 'custom': 410, '💪': 411, 'monica': 412, 'miss': 413, 'sound': 414, 'morning': 415, \"that's\": 416, 'x43': 417, 'definitely': 418, 'try': 419, 'tonight': 420, 'advice': 421, 'treviso': 422, 'concert': 423, 'city': 424, 'country': 425, \"i'll\": 426, 'start': 427, 'fine': 428, 'gorgeous': 429, 'xo': 430, 'oven': 431, 'roast': 432, 'garlic': 433, 'olive': 434, 'oil': 435, 'dry': 436, 'tomato': 437, 'dried': 438, 'basil': 439, 'century': 440, 'tuna': 441, 'right': 442, 'back': 443, 'atchya': 444, 'even': 445, 'almost': 446, 'chance': 447, 'cheer': 448, 'po': 449, 'ice': 450, 'cream': 451, 'agree': 452, '100': 453, 'hehehehe': 454, 'thats': 455, 'point': 456, 'stay': 457, 'home': 458, 'soon': 459, 'promise': 460, 'web': 461, 'whatsapp': 462, 'volta': 463, 'funcionar': 464, 'com': 465, 'iphone': 466, 'jailbroken': 467, 'later': 468, '34': 469, 'min': 470, 'leia': 471, 'appear': 472, 'hologram': 473, 'r2d2': 474, 'w': 475, 'message': 476, 'obi': 477, 'wan': 478, 'sit': 479, 'luke': 480, 'inter': 481, '3': 482, 'ucl': 483, 'arsenal': 484, 'small': 485, 'team': 486, 'passing': 487, '🚂': 488, 'dewsbury': 489, 'railway': 490, 'station': 491, 'dew': 492, 'west': 493, 'yorkshire': 494, '430': 495, 'smh': 496, '9:25': 497, 'live': 498, 'strange': 499, 'imagine': 500, 'megan': 501, 'masaantoday': 502, 'a4': 503, 'shweta': 504, 'tripathi': 505, '5': 506, '20': 507, 'kurta': 508, 'half': 509, 'number': 510, 'wsalelove': 511, 'ah': 512, 'larry': 513, 'anyway': 514, 'kinda': 515, 'goood': 516, 'life': 517, 'enn': 518, 'surely': 519, 'could': 520, 'warmup': 521, '15th': 522, 'bath': 523, 'dum': 524, 'andar': 525, 'ram': 526, 'sampath': 527, 'sona': 528, 'mohapatra': 529, 'samantha': 530, 'edward': 531, 'mein': 532, 'tulane': 533, 'razi': 534, 'wah': 535, 'josh': 536, 'always': 537, 'smile': 538, 'picture': 539, '16.20': 540, 'timing': 541, 'giveitup': 542, 'give': 543, 'gas': 544, 'subsidy': 545, 'initiative': 546, 'propose': 547, 'feeling': 548, 'delighted': 549, 'yesterday': 550, 'x42': 551, 'lmaoo': 552, 'song': 553, 'ever': 554, 'shall': 555, 'little': 556, 'throwback': 557, 'outlying': 558, 'island': 559, 'cheung': 560, 'chau': 561, 'mui': 562, 'wo': 563, 'totally': 564, 'different': 565, 'kfckitchentours': 566, 'kitchen': 567, 'clean': 568, \"i'm\": 569, 'amazed': 570, 'cusp': 571, 'test': 572, 'water': 573, 'reward': 574, 'arummzz': 575, \"let's\": 576, 'drive': 577, 'travel': 578, 'traveler': 579, 'yogyakarta': 580, 'jeep': 581, 'indonesia': 582, 'instamood': 583, 'wanna': 584, 'skype': 585, 'may': 586, 'nice': 587, 'friendly': 588, 'pretend': 589, 'film': 590, 'congratulation': 591, 'winner': 592, 'cheesydelights': 593, 'contest': 594, 'address': 595, 'guy': 596, 'marketing': 597, '24/7': 598, '14': 599, 'hour': 600, 'without': 601, 'delay': 602, 'actually': 603, 'easy': 604, 'guess': 605, 'train': 606, 'wd': 607, 'shift': 608, 'engine': 609, 'etc': 610, 'sunburn': 611, 'peel': 612, 'blog': 613, 'huge': 614, 'warm': 615, '☆': 616, 'complete': 617, 'triangle': 618, 'northern': 619, 'ireland': 620, 'sight': 621, 'smthng': 622, 'fr': 623, 'hug': 624, 'xoxo': 625, 'uu': 626, 'jaann': 627, 'topnewfollowers': 628, 'connect': 629, 'wonderful': 630, 'fluffy': 631, 'inside': 632, 'pirouette': 633, 'moose': 634, 'trip': 635, 'philly': 636, 'december': 637, \"i'd\": 638, 'dude': 639, 'x41': 640, 'question': 641, 'flaw': 642, 'pain': 643, 'negate': 644, 'strength': 645, 'solo': 646, 'move': 647, 'fav': 648, 'nirvana': 649, 'smell': 650, 'teen': 651, 'spirit': 652, 'rip': 653, 'amy': 654, 'winehouse': 655, 'couple': 656, 'tomhiddleston': 657, 'elizabetholsen': 658, 'yaytheylookgreat': 659, 'goodnight': 660, 'vid': 661, 'wake': 662, 'gonna': 663, 'shoot': 664, 'itty': 665, 'bitty': 666, 'teenie': 667, 'bikini': 668, 'much': 669, '4th': 670, 'together': 671, 'end': 672, 'xfiles': 673, 'content': 674, 'rain': 675, 'fabulous': 676, 'fantastic': 677, '♡': 678, 'jb': 679, 'forever': 680, 'belieber': 681, 'nighty': 682, 'bug': 683, 'bite': 684, 'bracelet': 685, 'idea': 686, 'foundry': 687, 'game': 688, 'sense': 689, 'pic': 690, 'eff': 691, 'phone': 692, 'woot': 693, 'derek': 694, 'use': 695, 'parkshare': 696, 'gloucestershire': 697, 'aaaahhh': 698, 'man': 699, 'traffic': 700, 'stress': 701, 'reliever': 702, \"how're\": 703, 'arbeloa': 704, 'turn': 705, '17': 706, 'omg': 707, 'difference': 708, 'say': 709, 'europe': 710, 'rise': 711, 'find': 712, 'hard': 713, 'believe': 714, 'uncountable': 715, 'coz': 716, 'unlimited': 717, 'course': 718, 'teampositive': 719, 'aldub': 720, '☕': 721, 'rita': 722, 'info': 723, \"we'd\": 724, 'way': 725, 'boy': 726, 'x40': 727, 'true': 728, 'sethi': 729, 'high': 730, 'exe': 731, 'skeem': 732, 'saam': 733, 'people': 734, 'polite': 735, 'izzat': 736, 'wese': 737, 'trust': 738, 'khawateen': 739, 'k': 740, 'sath': 741, 'mana': 742, 'kar': 743, 'deya': 744, 'evening': 745, 'sort': 746, 'smart': 747, 'hair': 748, 'tbh': 749, 'jacob': 750, 'g': 751, 'upgrade': 752, 'tee': 753, 'family': 754, 'reading': 755, 'person': 756, 'two': 757, 'conversation': 758, 'online': 759, 'mclaren': 760, 'fridayfeeling': 761, 'tgif': 762, 'square': 763, 'enix': 764, 'bissmillah': 765, 'ya': 766, 'allah': 767, \"we're\": 768, 'training': 769, 'socent': 770, 'startup': 771, 'drop': 772, 'youre': 773, 'arnd': 774, 'town': 775, 'basically': 776, 'piss': 777, 'cup': 778, 'also': 779, 'terrible': 780, 'complicated': 781, 'discussion': 782, 'snapchat': 783, 'lynettelowe': 784, 'kikmenow': 785, 'snapme': 786, 'hot': 787, 'amazon': 788, 'kikmeguys': 789, 'definately': 790, 'grow': 791, 'sport': 792, 'rt': 793, 'rakyat': 794, 'writing': 795, 'since': 796, 'mention': 797, 'fly': 798, 'fish': 799, 'promoted': 800, 'post': 801, 'cyber': 802, 'ourdaughtersourpride': 803, 'mypapamypride': 804, 'papa': 805, 'coach': 806, 'positive': 807, 'kha': 808, 'atleast': 809, 'x39': 810, 'mango': 811, \"lassi's\": 812, \"monty's\": 813, 'marvellous': 814, 'though': 815, 'suspect': 816, 'mean': 817, '24': 818, 'hr': 819, 'touch': 820, 'kepler': 821, '452b': 822, 'chalna': 823, 'hai': 824, 'thankyou': 825, 'hazel': 826, 'food': 827, 'market': 828, 'brooklyn': 829, 'pta': 830, 'awake': 831, 'okayy': 832, 'awww': 833, 'ha': 834, 'doc': 835, 'splendid': 836, 'spam': 837, 'folder': 838, 'amount': 839, 'nigeria': 840, 'claim': 841, 'rted': 842, 'legs': 843, 'hurt': 844, 'bad': 845, 'mine': 846, 'saturday': 847, 'thaaanks': 848, 'puhon': 849, 'happiness': 850, 'tnc': 851, 'prior': 852, 'notification': 853, 'fat': 854, 'co': 855, 'probably': 856, 'eat': 857, 'yuna': 858, 'tameside': 859, '´': 860, 'google': 861, 'account': 862, 'scouser': 863, 'everything': 864, 'zoe': 865, 'mate': 866, 'literally': 867, \"they're\": 868, 'sameee': 869, 'edgar': 870, 'update': 871, 'log': 872, 'bring': 873, 'abes': 874, 'meet': 875, 'x38': 876, 'sigh': 877, 'dreamily': 878, 'pout': 879, 'eye': 880, 'quacketyquack': 881, 'funny': 882, 'happen': 883, 'phil': 884, 'em': 885, 'del': 886, 'rodders': 887, 'else': 888, 'play': 889, 'gamejam': 890, 'irish': 891, 'literature': 892, 'inaccessible': 893, \"kareena's\": 894, 'fan': 895, 'brain': 896, 'dot': 897, 'braindots': 898, 'fair': 899, 'rush': 900, 'either': 901, 'brandi': 902, '18': 903, 'selfie': 904, 'carnival': 905, 'men': 906, 'put': 907, 'mask': 908, 'xavier': 909, 'forneret': 910, 'jennifer': 911, 'site': 912, 'free': 913, '50.000': 914, '8': 915, 'ball': 916, 'pool': 917, 'coin': 918, 'edit': 919, 'trish': 920, '♥': 921, 'gratefulness': 922, 'three': 923, 'grateful': 924, 'comment': 925, 'wakeup': 926, 'beside': 927, 'dirty': 928, 'sex': 929, 'lmaooo': 930, '😤': 931, 'louis': 932, \"he's\": 933, 'throw': 934, 'cause': 935, 'inspire': 936, 'ff': 937, 'twoofs': 938, 'gr8': 939, 'wkend': 940, 'kind': 941, 'exhausted': 942, 'word': 943, 'cheltenham': 944, 'area': 945, 'kale': 946, 'crisp': 947, 'ruin': 948, 'x37': 949, 'open': 950, 'worldwide': 951, 'outta': 952, 'sfvbeta': 953, 'vantastic': 954, 'xcylin': 955, 'bundle': 956, 'show': 957, 'internet': 958, 'price': 959, 'realisticly': 960, 'pay': 961, 'net': 962, 'education': 963, 'powerful': 964, 'weapon': 965, 'nelson': 966, 'mandela': 967, 'recent': 968, 'j': 969, 'chenab': 970, 'flow': 971, 'pakistan': 972, 'incredibleindia': 973, 'teenchoice': 974, 'choiceinternationalartist': 975, 'superjunior': 976, 'caught': 977, 'first': 978, 'salmon': 979, 'super-blend': 980, 'project': 981, 'youth@bipolaruk.org.uk': 982, 'awesome': 983, 'stream': 984, 'alma': 985, 'mater': 986, 'highschooldays': 987, 'clientvisit': 988, 'faith': 989, 'christian': 990, 'school': 991, 'lizaminnelli': 992, 'upcoming': 993, 'uk': 994, 'appearance': 995, '😄': 996, 'single': 997, 'hill': 998, 'every': 999, 'beat': 1000, 'wrong': 1001, 'ready': 1002, 'natural': 1003, 'pefumery': 1004, 'workshop': 1005, 'neals': 1006, 'yard': 1007, 'covent': 1008, 'tomorrow': 1009, 'fback': 1010, 'indo': 1011, 'harmos': 1012, 'americano': 1013, 'remember': 1014, 'aww': 1015, 'head': 1016, 'saw': 1017, 'dark': 1018, 'handshome': 1019, 'juga': 1020, 'hurray': 1021, 'meeting': 1022, 'hate': 1023, 'cant': 1024, 'decide': 1025, 'save': 1026, 'list': 1027, 'hiya': 1028, 'exec': 1029, 'loryn.good@lincs-chamber.co.uk': 1030, 'photo': 1031, 'thx': 1032, '4': 1033, 'china': 1034, 'homosexual': 1035, 'hyungbot': 1036, 'fam': 1037, 'mind': 1038, 'timetunnel': 1039, '1982': 1040, 'quite': 1041, 'radio': 1042, 'set': 1043, 'heart': 1044, 'hiii': 1045, 'jack': 1046, 'ily': 1047, '✨': 1048, 'domino': 1049, 'pub': 1050, 'heat': 1051, 'prob': 1052, 'sorry': 1053, 'hastily': 1054, 'type': 1055, 'screenshotting': 1056, 'pakistani': 1057, 'x36': 1058, '3points': 1059, 'dreamteam': 1060, 'gooo': 1061, 'bailey': 1062, 'pbb': 1063, '737gold': 1064, 'drink': 1065, 'old': 1066, '1/2': 1067, 'welsh': 1068, 'wale': 1069, 'yippee': 1070, '💟': 1071, 'bro': 1072, 'lord': 1073, 'michael': 1074, \"u're\": 1075, 'ure': 1076, 'bigot': 1077, 'usually': 1078, 'front': 1079, 'squat': 1080, 'dobar': 1081, 'dan': 1082, 'brand': 1083, 'heavy': 1084, 'musicology': 1085, '2015': 1086, 'spend': 1087, 'marathon': 1088, 'iflix': 1089, 'officially': 1090, 'graduate': 1091, 'cry': 1092, '__': 1093, 'yep': 1094, 'expert': 1095, 'bisexuality': 1096, 'minal': 1097, 'aidzin': 1098, 'yo': 1099, 'pi': 1100, 'cook': 1101, 'book': 1102, 'dinner': 1103, 'tough': 1104, 'choice': 1105, 'others': 1106, 'chill': 1107, 'smu': 1108, 'oval': 1109, 'basketball': 1110, 'player': 1111, 'whahahaha': 1112, 'soamazing': 1113, 'moment': 1114, 'onto': 1115, 'a5': 1116, 'wardrobe': 1117, 'user': 1118, 'teamred': 1119, 'apparently': 1120, 'hopefully': 1121, 'depends': 1122, 'greatly': 1123, 'design': 1124, 'ahhh': 1125, '7th': 1126, 'cinepambata': 1127, 'mechanic': 1128, 'official': 1129, 'form': 1130, 'download': 1131, 'ur': 1132, 'swishers': 1133, 'cop': 1134, 'ducktails': 1135, 'surreal': 1136, 'exposure': 1137, 'sotw': 1138, 'halesowen': 1139, 'blackcountryfair': 1140, 'street': 1141, 'assessment': 1142, 'mental': 1143, 'body': 1144, 'ooze': 1145, 'appeal': 1146, 'amassiveoverdoseofships': 1147, 'late': 1148, 'isi': 1149, 'chan': 1150, 'c': 1151, 'note': 1152, 'pkwalasawaal': 1153, 'gemma': 1154, 'orleans': 1155, 'fever': 1156, 'catch': 1157, 'geskenya': 1158, 'obamainkenya': 1159, 'magicalkenya': 1160, 'greatkenya': 1161, 'allgoodthingske': 1162, 'anime': 1163, 'umaru': 1164, 'singer': 1165, 'ship': 1166, 'order': 1167, 'room': 1168, 'car': 1169, 'hahaha': 1170, 'story': 1171, 'relate': 1172, 'label': 1173, 'batch': 1174, 'principal': 1175, 'due': 1176, 'march': 1177, 'wooftastic': 1178, 'receive': 1179, 'necessary': 1180, 'regret': 1181, 'rn': 1182, 'whatever': 1183, 'hat': 1184, 'success': 1185, 'abstinence': 1186, 'wtf': 1187, \"there's\": 1188, 'thrown': 1189, 'middle': 1190, 'repeat': 1191, 'relentlessly': 1192, 'approximately': 1193, 'oldschool': 1194, 'runescape': 1195, 'daaay': 1196, 'jumma_mubarik': 1197, 'frnds': 1198, 'stay_blessed': 1199, 'bless': 1200, 'pussycats': 1201, 'main': 1202, 'launch': 1203, 'pretoria': 1204, 'fahrinahmad': 1205, 'tengkuaaronshah': 1206, 'eksperimencinta': 1207, 'tykkäsin': 1208, 'videosta': 1209, 'month': 1210, 'hoodie': 1211, 'eeep': 1212, 'yay': 1213, 'sohappyrightnow': 1214, 'mmm': 1215, 'azz-sets': 1216, 'babe': 1217, 'feedback': 1218, 'gain': 1219, 'value': 1220, 'peaceful': 1221, 'refresh': 1222, 'manthan': 1223, 'tune': 1224, 'freshness': 1225, 'mother': 1226, 'determination': 1227, 'maxfreshmove': 1228, 'lonely': 1229, 'tattoo': 1230, 'friday.and': 1231, 'magnificent': 1232, 'e': 1233, 'achieve': 1234, 'rashmi': 1235, 'dedication': 1236, 'inspiration': 1237, 'happyfriday': 1238, 'nearly': 1239, 'retweeted': 1240, 'alert': 1241, 'da': 1242, 'dang': 1243, 'rad': 1244, 'fanart': 1245, 'massive': 1246, 'niamh': 1247, 'fennell': 1248, 'journalism': 1249, 'land': 1250, 'copying': 1251, 'paste': 1252, 'tweet': 1253, 'ariana': 1254, 'selena': 1255, 'gomez': 1256, 'tomlinson': 1257, 'payne': 1258, 'caradelevingne': 1259, '🌷': 1260, 'trade': 1261, 'tire': 1262, 'nope': 1263, 'apply': 1264, 'iamca': 1265, 'aftie': 1266, 'goodmorning': 1267, 'prokabaddi': 1268, 'koel': 1269, 'mallick': 1270, 'recite': 1271, 'national': 1272, 'anthem': 1273, '6': 1274, 'yournaturalleaders': 1275, 'youngnaturalleaders': 1276, 'mon': 1277, '27july': 1278, 'cumbria': 1279, 'flockstars': 1280, 'thur': 1281, '30july': 1282, 'itv': 1283, 'sleeptight': 1284, 'haveagoodday': 1285, 'leg': 1286, 'september': 1287, 'perhaps': 1288, 'bb': 1289, 'promote': 1290, 'full': 1291, 'album': 1292, 'fully': 1293, 'intend': 1294, 'write': 1295, 'possible': 1296, 'attack': 1297, '>:D': 1298, 'bird': 1299, 'teamadmicro': 1300, 'fridaydownpour': 1301, 'clear': 1302, 'rohit': 1303, 'queen': 1304, 'otwolgrandtrailer': 1305, 'sheer': 1306, 'fact': 1307, 'obama': 1308, 'innumerable': 1309, 'odds': 1310, 'president': 1311, 'ni': 1312, 'shauri': 1313, 'yako': 1314, 'memotohaters': 1315, 'sunday': 1316, 'pamper': 1317, \"t'was\": 1318, 'cabincrew': 1319, 'interview': 1320, 'langkawi': 1321, '1st': 1322, 'august': 1323, 'fulfil': 1324, 'fantasy': 1325, '👉': 1326, 'thinking': 1327, 'ex-twelebs': 1328, 'friends': 1329, 'apartment': 1330, 'makeover': 1331, 'brilliantly': 1332, 'happyyy': 1333, 'birthdaaayyy': 1334, 'kill': 1335, 'interested': 1336, 'internship': 1337, 'program': 1338, 'sadly': 1339, 'career': 1340, 'page': 1341, 'issue': 1342, 'sad': 1343, 'overwhelmingly': 1344, 'aha': 1345, 'beauts': 1346, '♬': 1347, 'win': 1348, 'deo': 1349, 'faaabulous': 1350, 'freebiefriday': 1351, 'aluminiumfree': 1352, 'stayfresh': 1353, 'john': 1354, 'worry': 1355, 'navigate': 1356, 'thnks': 1357, 'progrmr': 1358, '9pm': 1359, '9am': 1360, 'quit': 1361, 'hardly': 1362, 'surprising': 1363, 'roses': 1364, 'emotive': 1365, 'poetry': 1366, 'frequentflyer': 1367, 'break': 1368, 'apologize': 1369, 'kb': 1370, 'londondairy': 1371, 'icecream': 1372, 'experience': 1373, 'past': 1374, 'cover': 1375, 'sin': 1376, 'excited': 1377, \":')\": 1378, 'xxx': 1379, 'jim': 1380, 'chuckle': 1381, 'shopping': 1382, 'cake': 1383, 'doh': 1384, '500': 1385, 'subscriber': 1386, 'reach': 1387, 'scorch': 1388, 'summer': 1389, 'young': 1390, 'woman': 1391, 'stamen': 1392, 'expect': 1393, 'anything': 1394, 'less': 1395, 'tweeties': 1396, 'fab': 1397, 'dont': 1398, '-->': 1399, '10': 1400, 'loner': 1401, 'introduce': 1402, 'v': 1403, 'alter': 1404, 'understanding': 1405, 'spread': 1406, 'problem': 1407, 'supa': 1408, 'dupa': 1409, 'near': 1410, 'dartmoor': 1411, 'gold': 1412, 'colour': 1413, 'ok': 1414, 'someday': 1415, 'r': 1416, 'dii': 1417, 'n': 1418, 'forget': 1419, 'si': 1420, 'smf': 1421, 'ft': 1422, 'japanese': 1423, 'import': 1424, 'kitty': 1425, 'matching': 1426, 'stationary': 1427, 'draw': 1428, 'close': 1429, 'specialise': 1430, 'thermal': 1431, 'image': 1432, 'survey': 1433, '–': 1434, 'south': 1435, 'korea': 1436, 'scamper': 1437, 'alarm': 1438, \"ain't\": 1439, 'mad': 1440, 'chweina': 1441, 'xd': 1442, 'jotzh': 1443, 'waste': 1444, 'place': 1445, 'completely': 1446, 'worth': 1447, 'coat': 1448, 'beforehand': 1449, 'tho': 1450, 'foh': 1451, 'outside': 1452, 'holiday': 1453, 'menace': 1454, 'jojo': 1455, 'ta': 1456, 'accepted': 1457, 'guys': 1458, 'admin': 1459, 'lukris': 1460, '😘': 1461, 'momma': 1462, 'bear': 1463, '❤': 1464, '️': 1465, 'redo': 1466, '8th': 1467, 'v.ball': 1468, 'atm': 1469, 'retweets': 1470, 'build': 1471, 'pack': 1472, 'suitcase': 1473, 'hang-copying': 1474, 'translation': 1475, \"dostoevsky's\": 1476, 'voucher': 1477, 'bugatti': 1478, 'bra': 1479, 'مطعم_هاشم': 1480, 'yummy': 1481, 'a7la': 1482, 'bdayt': 1483, 'mnwreeen': 1484, 'jazz': 1485, 'truck': 1486, 'x34': 1487, 'speak': 1488, 'pbevent': 1489, 'hq': 1490, 'yoona': 1491, 'hairpin': 1492, 'otp': 1493, 'collection': 1494, 'mastership': 1495, 'honey': 1496, 'paindo': 1497, 'await': 1498, 'report': 1499, 'manny': 1500, 'asshole': 1501, 'brijresidency': 1502, 'structure': 1503, '156': 1504, 'unit': 1505, 'encompass': 1506, 'bhk': 1507, 'flat': 1508, '91': 1509, '975-580-': 1510, '444': 1511, 'honor': 1512, 'curry': 1513, 'clash': 1514, 'milano': 1515, '👌': 1516, 'followback': 1517, ':-D': 1518, 'legit': 1519, 'loser': 1520, 'dead': 1521, 'starsquad': 1522, '⭐': 1523, 'news': 1524, 'utc': 1525, 'flume': 1526, 'kaytranada': 1527, 'alunageorge': 1528, 'ticket': 1529, 'kms': 1530, 'certainty': 1531, 'solve': 1532, 'faster': 1533, '👊': 1534, 'hurry': 1535, 'totem': 1536, 'somewhere': 1537, 'alice': 1538, 'dog': 1539, 'cat': 1540, 'goodwynsgoodies': 1541, 'ugh': 1542, 'fade': 1543, 'moan': 1544, 'leeds': 1545, 'jozi': 1546, 'wasnt': 1547, 'fifth': 1548, 'available': 1549, 'tix': 1550, 'pa': 1551, 'ba': 1552, 'ng': 1553, 'atl': 1554, 'coldplay': 1555, 'favorite': 1556, 'scientist': 1557, 'yellow': 1558, 'atlas': 1559, 'yein': 1560, 'selos': 1561, 'jabongatpumaurbanstampede': 1562, 'an': 1563, '7': 1564, 'timely': 1565, 'arrival': 1566, 'waiter': 1567, 'bill': 1568, 'sir': 1569, 'title': 1570, 'pocket': 1571, 'wripped': 1572, 'jean': 1573, 'connie': 1574, 'crew': 1575, 'staff': 1576, 'sweetan': 1577, 'ask': 1578, 'filming': 1579, 'mum': 1580, 'beg': 1581, 'soprano': 1582, 'ukraine': 1583, 'x33': 1584, 'olly': 1585, 'disney.arts': 1586, 'elmoprinssi': 1587, 'tired': 1588, 'salsa': 1589, 'dance': 1590, 'tell': 1591, 'truth': 1592, 'pls': 1593, '4-6': 1594, 'interest': 1595, '2nd': 1596, 'blogiversary': 1597, 'review': 1598, 'cutie': 1599, 'bohol': 1600, 'briliant': 1601, 'key': 1602, 'annual': 1603, 'productive': 1604, 'far': 1605, 'spin': 1606, 'voice': 1607, '\\U000fe334': 1608, 'yeheyy': 1609, 'pinya': 1610, 'whoooah': 1611, 'trance': 1612, 'lover': 1613, 'subject': 1614, 'physic': 1615, 'stop': 1616, 'ब': 1617, 'matter': 1618, 'jungle': 1619, 'accommodate': 1620, 'secret': 1621, 'behind': 1622, 'sandroforceo': 1623, 'ceo': 1624, '1month': 1625, 'swag': 1626, 'mia': 1627, 'workinprogress': 1628, 'finnigan': 1629, 'loyal': 1630, 'royal': 1631, 'fotoset': 1632, 'reusful': 1633, 'seem': 1634, 'somebody': 1635, 'sell': 1636, 'understand': 1637, 'muntu': 1638, 'another': 1639, 'gem': 1640, 'falcos': 1641, 'supersmash': 1642, 'hotnsexy': 1643, 'friskyfriday': 1644, 'beach': 1645, 'movie': 1646, 'crop': 1647, 'nash': 1648, 'tissue': 1649, 'chocolate': 1650, 'tea': 1651, 'hannibal': 1652, 'episode': 1653, 'hotbed': 1654, 'bush': 1655, 'classicassures': 1656, 'thrill': 1657, 'international': 1658, 'assignment': 1659, 'aerial': 1660, 'camera': 1661, 'operator': 1662, 'wales': 1663, 'boom': 1664, 'hong': 1665, 'kong': 1666, 'ferry': 1667, 'central': 1668, 'girlfriend': 1669, 'after-work': 1670, 'dj': 1671, 'resto': 1672, 'drinkt': 1673, 'koffie': 1674, 'a6': 1675, 'stargate': 1676, 'atlantis': 1677, 'muaahhh': 1678, 'ohh': 1679, 'hii': 1680, '🙈': 1681, 'di': 1682, 'nagsend': 1683, 'yung': 1684, 'ko': 1685, '</3': 1686, 'ulit': 1687, '🎉': 1688, '🎈': 1689, 'ugly': 1690, 'leggete': 1691, 'qui': 1692, 'per': 1693, 'la': 1694, 'mar': 1695, 'encourage': 1696, 'employer': 1697, 'board': 1698, 'sticker': 1699, 'sponsor': 1700, 'prize': 1701, '(:': 1702, 'milo': 1703, 'aurini': 1704, 'juicebro': 1705, 'fucking': 1706, 'pillar': 1707, 'respective': 1708, 'boii': 1709, 'smashingbook': 1710, 'bible': 1711, 'ill': 1712, 'sick': 1713, 'lamo': 1714, 'fangirl': 1715, 'platonic': 1716, 'science': 1717, 'resident': 1718, 'servicewithasmile': 1719, 'fams': 1720, 'bloodline': 1721, 'husky': 1722, 'obituary': 1723, 'advert': 1724, 'goofingaround': 1725, 'madness': 1726, 'bollywood': 1727, 'giveaway': 1728, 'dah': 1729, 'nothing': 1730, 'bitterness': 1731, 'anger': 1732, 'hatred': 1733, 'towards': 1734, 'pure': 1735, 'indifference': 1736, 'suite': 1737, 'zach': 1738, 'cody': 1739, 'deliver': 1740, 'ac': 1741, 'excellence': 1742, 'producer': 1743, 'boggling': 1744, 'fatigue': 1745, 'baareeq': 1746, 'gamedev': 1747, 'hobby': 1748, 'tweenie_fox': 1749, 'click': 1750, 'accessory': 1751, 'tamang': 1752, 'hinala': 1753, 'niam': 1754, 'selfieee': 1755, 'especially': 1756, 'lass': 1757, 'aling': 1758, 'swim': 1759, 'perfection': 1760, 'bout': 1761, 'goodbye': 1762, 'feminist': 1763, 'fight': 1764, 'snobby': 1765, 'bitch': 1766, 'caroline': 1767, 'mighty': 1768, '🔥': 1769, 'hbd': 1770, 'follback': 1771, 'jog': 1772, 'remote': 1773, 'newly': 1774, 'ebay': 1775, 'store': 1776, 'disneyinfinity': 1777, 'starwars': 1778, 'character': 1779, 'preorder': 1780, 'starter': 1781, 'hit': 1782, 'snap': 1783, 'homies': 1784, 'skin': 1785, 'bday': 1786, 'chant': 1787, 'jai': 1788, 'italy': 1789, 'fast': 1790, 'heeeyyy': 1791, 'woah': 1792, '★': 1793, '😊': 1794, 'whenever': 1795, 'ang': 1796, 'kiss': 1797, 'philippine': 1798, 'package': 1799, 'bruise': 1800, 'rib': 1801, '😀': 1802, '😁': 1803, '😂': 1804, '😃': 1805, '😅': 1806, '😉': 1807, 'tombraider': 1808, 'hype': 1809, 'thejuiceinthemix': 1810, 'rela': 1811, 'building': 1812, 'low': 1813, 'priority': 1814, 'match': 1815, 'harry': 1816, 'bc': 1817, 'opportune': 1818, 'collapse': 1819, 'chaotic': 1820, 'cosas': 1821, '<---': 1822, 'alliteration': 1823, 'oppayaa': 1824, \"how's\": 1825, 'natgeo': 1826, 'lick': 1827, 'elbow': 1828, '. .': 1829, 'interesting': 1830, '“': 1831, 'emu': 1832, 'stoke': 1833, \"people's\": 1834, 'approval': 1835, \"god's\": 1836, 'jisung': 1837, 'kid': 1838, 'sunshine': 1839, 'mm': 1840, 'nicola': 1841, 'brighten': 1842, 'helen': 1843, 'brian': 1844, '2-3': 1845, 'australia': 1846, 'ol': 1847, 'bone': 1848, 'creaking': 1849, 'abuti': 1850, 'tweetland': 1851, 'android': 1852, 'xmas': 1853, 'skyblock': 1854, 'standing': 1855, 'bcause': 1856, '2009': 1857, 'die': 1858, 'twitch': 1859, 'sympathy': 1860, 'laugh': 1861, 'unnieee': 1862, 'nuka': 1863, 'penacova': 1864, 'djset': 1865, 'edm': 1866, 'kizomba': 1867, 'latinhouse': 1868, 'housemusic': 1869, 'portugal': 1870, 'wild': 1871, 'ride': 1872, 'anytime': 1873, 'taste': 1874, 'yer': 1875, 'mtn': 1876, 'maganda': 1877, 'mistress': 1878, 'saphire': 1879, 'busy': 1880, '4000': 1881, 'instagram': 1882, 'among': 1883, 'coconut': 1884, 'sambal': 1885, 'mussel': 1886, 'recipe': 1887, 'kalin': 1888, 'mixcloud': 1889, 'sarcasm': 1890, 'chelsea': 1891, 'he': 1892, 'useless': 1893, 'thursday': 1894, 'hang': 1895, 'hehe': 1896, 'benson': 1897, 'facebook': 1898, 'solid': 1899, '16/17': 1900, '30': 1901, '°': 1902, '😜': 1903, 'maryhicks': 1904, 'kikmeboys': 1905, 'photooftheday': 1906, 'musicbiz': 1907, 'sheskindahot': 1908, 'fleekile': 1909, 'mbalula': 1910, 'africa': 1911, 'mexican': 1912, 'scar': 1913, 'office': 1914, 'donut': 1915, 'foiegras': 1916, 'despite': 1917, 'weather': 1918, 'wedding': 1919, 'tony': 1920, 'stark': 1921, 'incredible': 1922, 'poem': 1923, 'bubble': 1924, 'dale': 1925, 'billion': 1926, 'magical': 1927, 'op': 1928, 'cast': 1929, 'vote': 1930, 'election': 1931, 'jcreport': 1932, 'piggin': 1933, 'peace': 1934, 'botanical': 1935, 'soap': 1936, 'upload': 1937, 'freshly': 1938, '3weeks': 1939, 'heal': 1940, 'exciting': 1941, 'tobi-bro': 1942, 'isp': 1943, 'steel': 1944, 'wednesday': 1945, 'swear': 1946, 'earlier': 1947, 'cam': 1948, '😭': 1949, 'except': 1950, \"masha'allah\": 1951, 'french': 1952, 'wwat': 1953, 'france': 1954, 'yaaay': 1955, 'beiruting': 1956, 'coffee': 1957, 'panda': 1958, 'eonnie': 1959, 'favourite': 1960, 'soda': 1961, 'fuller': 1962, 'shit': 1963, 'healthy': 1964, '💓': 1965, 'rettweet': 1966, 'mvg': 1967, 'valuable': 1968, 'madrid': 1969, 'sore': 1970, 'bergerac': 1971, 'u21': 1972, 'individual': 1973, 'excellent': 1974, 'adam': 1975, \"beach's\": 1976, 'suicide': 1977, 'squad': 1978, 'fond': 1979, 'christopher': 1980, 'initially': 1981, 'cocky': 1982, 'prove': 1983, \"attitude's\": 1984, 'improve': 1985, 'suggest': 1986, 'date': 1987, 'indeed': 1988, 'happys': 1989, 'intelligent': 1990, 'cs': 1991, 'certain': 1992, 'exam': 1993, 'forgot': 1994, 'home-based': 1995, 'knee': 1996, 'sale': 1997, 'fleur': 1998, 'dress': 1999, 'readystock_hijabmart': 2000, 'idr': 2001, '325.000': 2002, '200.000': 2003, 'tompolo': 2004, 'aim': 2005, 'cannot': 2006, 'buyer': 2007, 'disappoint': 2008, 'paper': 2009, 'slacking': 2010, 'crack': 2011, 'particularly': 2012, 'striking': 2013, '31': 2014, 'mam': 2015, 'feytyaz': 2016, 'instant': 2017, 'stiffening': 2018, 'ricky_febs': 2019, 'grindea': 2020, 'courier': 2021, 'crypt': 2022, 'possibly': 2023, 'arma': 2024, 'record': 2025, 'gosh': 2026, 'limbo': 2027, 'retweeting': 2028, 'orchard': 2029, 'art': 2030, 'super': 2031, 'karachi': 2032, 'ka': 2033, 'venice': 2034, 'several': 2035, 'part': 2036, 'witness': 2037, 'accumulate': 2038, 'maroon': 2039, 'cocktail': 2040, '0-100': 2041, 'quick': 2042, '1100d': 2043, 'auto-focus': 2044, 'manual': 2045, 'vein': 2046, 'crackle': 2047, 'glaze': 2048, 'layout': 2049, 'bomb': 2050, 'social': 2051, 'website': 2052, 'pake': 2053, 'joim': 2054, 'fee': 2055, 'troop': 2056, 'beauty': 2057, 'mail': 2058, 'ladolcevitainluxembourg@hotmail.com': 2059, 'prrequest': 2060, 'journorequest': 2061, 'the_madstork': 2062, 'shaun': 2063, 'bot': 2064, 'chloe': 2065, 'actress': 2066, 'away': 2067, 'wicked': 2068, 'hola': 2069, 'juan': 2070, 'sending': 2071, 'houston': 2072, 'tx': 2073, 'jenni': 2074, \"year's\": 2075, 'stumble': 2076, 'upon': 2077, 'prob.nice': 2078, 'choker': 2079, 'btw': 2080, 'seouljins': 2081, 'photoset': 2082, 'sadomasochistsparadise': 2083, 'wynter': 2084, 'bottom': 2085, 'outtake': 2086, 'sadomasochist': 2087, 'paradise': 2088, 'cuties': 2089, 'ty': 2090, 'bby': 2091, 'clip': 2092, 'lose': 2093, 'cypher': 2094, 'amen': 2095, 'x32': 2096, 'plant': 2097, 'allow': 2098, 'corner': 2099, 'addict': 2100, 'gurl': 2101, 'suck': 2102, 'special': 2103, 'owe': 2104, 'daniel': 2105, 'ape': 2106, 'saar': 2107, 'ahead': 2108, 'verse': 2109, 'butterfly': 2110, 'bonus': 2111, 'fill': 2112, 'tear': 2113, 'laughter': 2114, '5sos': 2115, 'yummmyyy': 2116, 'dosa': 2117, 'unless': 2118, 'achi': 2119, 'youuu': 2120, 'bawi': 2121, 'ako': 2122, 'queenesther': 2123, 'sharp': 2124, 'wonder': 2125, 'poldi': 2126, 'cimbom': 2127, 'buddy': 2128, 'bruhhh': 2129, 'daddy': 2130, '”': 2131, 'communal': 2132, 'knowledge': 2133, 'attention': 2134, '1tb': 2135, 'bank': 2136, 'credit': 2137, 'department': 2138, 'anz': 2139, 'extreme': 2140, 'offshoring': 2141, 'absolutely': 2142, 'classic': 2143, 'gottolovebanks': 2144, 'yup': 2145, 'in-shaa-allah': 2146, 'dua': 2147, 'thru': 2148, 'aameen': 2149, '4/5': 2150, 'coca': 2151, 'cola': 2152, 'fanta': 2153, 'pepsi': 2154, 'sprite': 2155, 'alls': 2156, 'sweeety': 2157, ';-)': 2158, 'welcometweet': 2159, 'psygustokita': 2160, 'setup': 2161, 'wet': 2162, 'foot': 2163, 'carpet': 2164, 'judgmental': 2165, 'hypocritical': 2166, 'narcissist': 2167, 'jumpsuit': 2168, 'bt': 2169, 'denim': 2170, 'verge': 2171, 'owl': 2172, 'constant': 2173, 'run': 2174, 'sia': 2175, 'count': 2176, 'brilliant': 2177, 'teacher': 2178, 'comparative': 2179, 'religion': 2180, 'rant': 2181, 'student': 2182, 'benchers': 2183, '1/5': 2184, 'porsche': 2185, 'paddock': 2186, 'budapestgp': 2187, 'johnyherbert': 2188, 'roll': 2189, 'porschesupercup': 2190, 'koyal': 2191, 'melody': 2192, 'unexpected': 2193, 'create': 2194, 'memory': 2195, '35': 2196, 'eps': 2197, 'wirh': 2198, 'arc': 2199, 'x31': 2200, 'wolf': 2201, 'fulfill': 2202, 'desire': 2203, 'ameen': 2204, 'kca': 2205, 'votejkt': 2206, '48id': 2207, 'helpinggroupdms': 2208, 'quote': 2209, 'weird': 2210, 'dp': 2211, 'wife': 2212, 'poor': 2213, 'chick': 2214, 'guide': 2215, 'zonzofox': 2216, 'bhaiya': 2217, 'brother': 2218, 'lucky': 2219, 'patty': 2220, 'elaborate': 2221, 'kuching': 2222, 'rate': 2223, 'merdeka': 2224, 'palace': 2225, 'hotel': 2226, 'plusmiles': 2227, 'service': 2228, 'hahahaa': 2229, 'nex': 2230, 'safe': 2231, 'gwd': 2232, 'shes': 2233, 'okok': 2234, '33': 2235, 'idiot': 2236, 'chaerin': 2237, 'unnie': 2238, 'viable': 2239, 'alternative': 2240, 'nowadays': 2241, 'pass': 2242, 'ip': 2243, 'tombow': 2244, 'abt': 2245, 'friyay': 2246, 'smug': 2247, 'marrickville': 2248, 'public': 2249, 'ten': 2250, 'ago': 2251, 'eighteen': 2252, 'auvssscr': 2253, 'ncaaseason': 2254, 'slow': 2255, 'popsicle': 2256, 'soft': 2257, 'melt': 2258, 'mouth': 2259, 'thankyouuu': 2260, 'dianna': 2261, 'ngga': 2262, 'usah': 2263, 'dipikirin': 2264, 'elah': 2265, 'easily': 2266, \"who's\": 2267, 'entp': 2268, 'killin': 2269, 'meme': 2270, 'worthy': 2271, 'shot': 2272, 'emon': 2273, 'decent': 2274, 'outdoor': 2275, 'rave': 2276, 'dv': 2277, 'aku': 2278, 'bakal': 2279, 'liat': 2280, 'kak': 2281, 'merry': 2282, 'tv': 2283, 'outfit': 2284, '--->': 2285, 'fashionfriday': 2286, 'angle.nelson': 2287, 'cheap': 2288, 'mymonsoonstory': 2289, 'tree': 2290, 'lotion': 2291, 'moisturize': 2292, 'important': 2293, 'monsoon': 2294, 'whoop': 2295, 'romantic': 2296, 'valencia': 2297, 'daaru': 2298, 'party': 2299, 'chaddi': 2300, 'bros': 2301, 'wonderful.great': 2302, 'closely': 2303, 'trim': 2304, 'pubes': 2305, 'mi': 2306, 'tio': 2307, 'sinaloa': 2308, 'arre': 2309, 'stylish': 2310, 'trendy': 2311, 'kim': 2312, 'fabfriday': 2313, 'facetime': 2314, 'calum': 2315, 'constantly': 2316, 'announce': 2317, 'filbarbarian': 2318, 'beer': 2319, 'broken': 2320, 'arm': 2321, 'testicle': 2322, 'light': 2323, 'katerina': 2324, 'maniataki': 2325, 'ahh': 2326, 'alright': 2327, 'worthwhile': 2328, 'judging': 2329, 'tech': 2330, 'window': 2331, 'stupid': 2332, 'plugin': 2333, 'bass': 2334, 'slap': 2335, '6pm': 2336, 'door': 2337, 'vip': 2338, 'general': 2339, 'seat': 2340, 'early': 2341, 'london': 2342, 'toptravelcentar': 2343, 'ttctop': 2344, 'lux': 2345, 'luxurytravel': 2346, 'beograd': 2347, 'srbija': 2348, 'putovanja': 2349, 'wendy': 2350, 'provide': 2351, 'fresh': 2352, 'drainage': 2353, 'homebound': 2354, 'hahahays': 2355, 'yeeeah': 2356, 'moar': 2357, 'kittehs': 2358, 'incoming': 2359, 'tower': 2360, 'yippeee': 2361, 'scrummy': 2362, 'bio': 2363, 'mcpe': 2364, '->': 2365, 'vainglory': 2366, 'driver': 2367, '6:01': 2368, 'lilydale': 2369, 'f': 2370, 'raise': 2371, 'magicalmysterytour': 2372, 'chek': 2373, 'rule': 2374, 'weebly': 2375, 'donetsk': 2376, 'earth': 2377, 'personalise': 2378, 'wrap': 2379, 'business': 2380, 'stationery': 2381, 'adrian': 2382, 'parcel': 2383, 'tuesday': 2384, 'pris': 2385, '80': 2386, 'wz': 2387, 'pattern': 2388, 'cut': 2389, 'buttonhole': 2390, 'finishing': 2391, '4my': 2392, 'designer': 2393, 'famous': 2394, 'client': 2395, 'p': 2396, 'alive': 2397, 'trial': 2398, 'spm': 2399, 'dinooo': 2400, 'cardio': 2401, 'steak': 2402, 'cue': 2403, 'laptop': 2404, 'excite': 2405, 'guinea': 2406, 'pig': 2407, 'bestfriends': 2408, 'salamat': 2409, 'sa': 2410, 'mga': 2411, 'nag.greet': 2412, 'appreciated': 2413, 'guise': 2414, 'godbless': 2415, 'crush': 2416, 'apple': 2417, 'ga': 2418, 'deserve': 2419, 'charles': 2420, 'workhard': 2421, 'model': 2422, 'forrit': 2423, 'bread': 2424, 'bacon': 2425, 'butter': 2426, 'afang': 2427, 'soup': 2428, 'semo': 2429, 'brb': 2430, 'force': 2431, 'doesnt': 2432, 'tato': 2433, 'bulat': 2434, 'discuss': 2435, 'suggestion': 2436, 'concerned': 2437, 'snake': 2438, 'perform': 2439, 'con': 2440, 'todayyy': 2441, 'max': 2442, 'gaza': 2443, 'retweet': 2444, 'bbb': 2445, 'peacefully': 2446, 'pc': 2447, '22': 2448, 'legal': 2449, 'ditch': 2450, 'tory': 2451, 'bajrangibhaijaanhighestweek': 2452, \"s'okay\": 2453, 'andy': 2454, 'you-and': 2455, 'return': 2456, 'tuitutil': 2457, 'bud': 2458, 'learn': 2459, 'takeaway': 2460, 'slept': 2461, 'instead': 2462, '1hr': 2463, 'genial': 2464, 'competition': 2465, 'yosh': 2466, 'procrastinate': 2467, 'plus': 2468, 'sorting': 2469, 'kfc': 2470, 'itunes': 2471, 'dedicatedfan': 2472, '💜': 2473, 'daft': 2474, 'teethe': 2475, 'trouble': 2476, 'huxley': 2477, 'basket': 2478, 'ben': 2479, 'gamer': 2480, 'active': 2481, '120': 2482, 'distance': 2483, 'suitable': 2484, 'final': 2485, 'stockholm': 2486, 'zack': 2487, 'destroy': 2488, 'heel': 2489, 'claw': 2490, 'q': 2491, 'blonde': 2492, 'box': 2493, 'cheerio': 2494, 'seed': 2495, 'cutest': 2496, 'ffback': 2497, 'spotify': 2498, \"we've\": 2499, 'vc': 2500, 'tgp': 2501, 'race': 2502, 'average': 2503, \"joe's\": 2504, 'bluejays': 2505, 'vinylbear': 2506, 'pal': 2507, 'furbaby': 2508, 'luff': 2509, 'mega': 2510, 'retail': 2511, 'boot': 2512, 'whsmith': 2513, 'ps3': 2514, 'shannon': 2515, 'na': 2516, 'redecorate': 2517, 'bob': 2518, 'ellie': 2519, 'mairi': 2520, 'workout': 2521, 'impair': 2522, 'uggghhh': 2523, 'dam': 2524, 'dun': 2525, 'eczema': 2526, 'sufferer': 2527, 'ndee': 2528, 'pleasure': 2529, 'publilius': 2530, 'syrus': 2531, 'fear': 2532, 'death': 2533, 'dread': 2534, 'fell': 2535, 'fuk': 2536, 'unblock': 2537, 'manually': 2538, 'tweak': 2539, 'php': 2540, 'fall': 2541, 'oomf': 2542, 'pippa': 2543, 'hschool': 2544, 'bus': 2545, 'cardi': 2546, 'everyday': 2547, 'everytime': 2548, 'hk': 2549, \"why'd\": 2550, 'acorn': 2551, 'originally': 2552, 'c64': 2553, 'apart': 2554, 'cpu': 2555, 'considerably': 2556, 'advanced': 2557, 'onair': 2558, 'bay': 2559, 'hold': 2560, 'river': 2561, '0878 0388': 2562, '1033': 2563, '0272 3306': 2564, '70': 2565, 'rescue': 2566, 'mutt': 2567, 'confirm': 2568, 'delivery': 2569, 'switch': 2570, 'lap': 2571, 'optimize': 2572, 'lu': 2573, ':|': 2574, 'tweetofthedecade': 2575, ':P': 2576, 'class': 2577, 'happiest': 2578, 'bbmme': 2579, 'pin': 2580, '7df9e60a': 2581, 'bbm': 2582, 'bbmpin': 2583, 'addmeonbbm': 2584, 'addme': 2585, \"today's\": 2586, 'normal': 2587, 'menu': 2588, 'marry': 2589, 'glenn': 2590, 'whats': 2591, 'height': 2592, \"sculptor's\": 2593, 'ti5': 2594, 'dota': 2595, 'nudge': 2596, 'spot': 2597, 'tasty': 2598, 'hilly': 2599, 'cycle': 2600, 'england': 2601, 'scotlandismassive': 2602, 'gen': 2603, 'vikk': 2604, 'fna': 2605, 'mombasa': 2606, 'tukutanemombasa': 2607, '100reasonstovisitmombasa': 2608, 'karibumombasa': 2609, 'hanbin': 2610, 'certainly': 2611, 'goosnight': 2612, 'kindly': 2613, 'familiar': 2614, 'jealous': 2615, 'tent': 2616, 'yea': 2617, 'cozy': 2618, 'phenomenal': 2619, 'collab': 2620, 'birth': 2621, 'behave': 2622, 'monster': 2623, 'spree': 2624, '000': 2625, 'tank': 2626, 'outstanding': 2627, 'donation': 2628, 'h': 2629, 'contestkiduniya': 2630, 'mfundo': 2631, 'oche': 2632, 'hun': 2633, 'inner': 2634, 'nerd': 2635, 'tame': 2636, 'insidious': 2637, 'logic': 2638, 'math': 2639, 'channel': 2640, 'continue': 2641, 'doubt': 2642, '300': 2643, 'sub': 2644, '200': 2645, 'subs': 2646, 'forgiven': 2647, 'wonderfuls': 2648, 'mannerfuls': 2649, 'yhooo': 2650, 'ngi': 2651, 'mood': 2652, 'push': 2653, 'limit': 2654, 'obakeng': 2655, 'goat': 2656, 'alhamdullilah': 2657, 'pebble': 2658, 'engross': 2659, 'bing': 2660, 'scream': 2661, 'whole': 2662, 'wide': 2663, '🌎': 2664, '😧': 2665, 'wat': 2666, 'muahhh': 2667, 'pausetime': 2668, 'drift': 2669, 'loose': 2670, 'campaign': 2671, 'kickstarter': 2672, 'article': 2673, 'absolute': 2674, 'jenna': 2675, 'bellybutton': 2676, 'innie': 2677, 'outie': 2678, 'havent': 2679, 'delish': 2680, 'joselito': 2681, 'freya': 2682, 'nth': 2683, 'latepost': 2684, 'lupet': 2685, 'mo': 2686, 'eric': 2687, 'askaman': 2688, 'helpful': 2689, 'alternatively': 2690, '150': 2691, '0345': 2692, '454': 2693, '111': 2694, 'webz': 2695, 'oops': 2696, \"they'll\": 2697, 'realise': 2698, 'anymore': 2699, 'carmel': 2700, 'decision': 2701, 'matt': 2702, 'probs': 2703, '@commonculture': 2704, '@connorfranta': 2705, 'honestly': 2706, 'explain': 2707, 'relationship': 2708, 'pick': 2709, 'tessnzach': 2710, 'paperboy': 2711, 'honest': 2712, 'reassure': 2713, 'personal': 2714, 'mubank': 2715, \"dongwoo's\": 2716, 'bright': 2717, 'tommorow': 2718, 'newyork': 2719, 'magic': 2720, 'lolll': 2721, 'twinx': 2722, '16': 2723, 'path': 2724, 'firmansyahbl': 2725, 'usual': 2726, 'procedure': 2727, 'grim': 2728, 'fandango': 2729, 'ordinary': 2730, 'extraordinary': 2731, 'bos': 2732, 'birmingham': 2733, 'oracle': 2734, 'samosa': 2735, 'fireball': 2736, 'shoe': 2737, 'serve': 2738, 'sushi': 2739, 'shoeshi': 2740, '�': 2741, 'lymond': 2742, 'philippa': 2743, 'novel': 2744, 'tara': 2745, '. . .': 2746, 'aur': 2747, 'han': 2748, 'imran': 2749, 'khan': 2750, '63': 2751, 'agaaain': 2752, 'doli': 2753, 'siregar': 2754, 'ninh': 2755, 'size': 2756, 'geekiest': 2757, 'geek': 2758, 'wallet': 2759, 'das': 2760, 'request': 2761, 'medium': 2762, 'rally': 2763, 'rotate': 2764, 'direction': 2765, 'eek': 2766, 'red': 2767, 'beijing': 2768, 'meni': 2769, 'tebrik': 2770, 'etdi': 2771, '700': 2772, '💗': 2773, 'rod': 2774, 'embrace': 2775, 'actor': 2776, 'aplomb': 2777, 'foreveralone': 2778, 'mysummer': 2779, '01482': 2780, '333505': 2781, 'hahahaha': 2782, 'wear': 2783, 'uniform': 2784, 'evil': 2785, 'owww': 2786, 'choo': 2787, 'chweet': 2788, 'shorthaired': 2789, 'oscar': 2790, 'realize': 2791, 'harmony': 2792, 'judge': 2793, 'denerivery': 2794, '506': 2795, 'kiksexting': 2796, 'kikkomansabor': 2797, 'killer': 2798, 'henessydiaries': 2799, 'journey': 2800, 'band': 2801, 'plz': 2802, 'convo': 2803, '11': 2804, 'vault': 2805, 'expand': 2806, 'vinny': 2807, 'money': 2808, 'hahahahaha': 2809, '50cents': 2810, 'repay': 2811, 'debt': 2812, 'smiling': 2813, 'evet': 2814, 'wifi': 2815, 'lifestyle': 2816, 'qatarday': 2817, '. ..': 2818, '🌞': 2819, 'girly': 2820, 'india': 2821, 'innovate': 2822, 'volunteer': 2823, 'saran': 2824, 'drama': 2825, 'genre': 2826, 'romance': 2827, 'comedy': 2828, 'leanneriner': 2829, '19': 2830, 'porno': 2831, 'l4l': 2832, 'weloveyounamjoon': 2833, 'homey': 2834, 'kenya': 2835, 'emotional': 2836, 'roller': 2837, 'coaster': 2838, 'aspect': 2839, 'najam': 2840, 'confession': 2841, 'ad': 2842, 'pricelessantique': 2843, 'takesonetoknowone': 2844, 'extra': 2845, 'ucount': 2846, 'ji': 2847, 'turkish': 2848, 'crap': 2849, 'burn': 2850, '80x': 2851, 'airline': 2852, 'sexy': 2853, 'yello': 2854, 'gail': 2855, 'yael': 2856, 'lesson': 2857, 'en': 2858, 'manos': 2859, 'hand': 2860, 'manager': 2861, 'reader': 2862, 'dnt': 2863, 'ideal': 2864, 'weekly': 2865, 'idol': 2866, 'pose': 2867, 'shortlist': 2868, 'dominion': 2869, 'picnic': 2870, 'tmrw': 2871, 'nobody': 2872, 'jummamubarak': 2873, 'shower': 2874, 'shalwarkameez': 2875, 'itter': 2876, 'offer': 2877, 'jummaprayer': 2878, 'af': 2879, 'display': 2880, 'enable': 2881, 'company': 2882, 'peep': 2883, 'tweeps': 2884, 'folow': 2885, '2k': 2886, 'ohhh': 2887, 'teaser': 2888, 'airecs': 2889, '009': 2890, 'acid': 2891, 'mouse': 2892, 'ep': 2893, '31st': 2894, 'include': 2895, 'robin': 2896, 'rough': 2897, 'control': 2898, 'remixes': 2899, 'rts': 2900, 'faves': 2901, 'toss': 2902, 'lady': 2903, '🐑': 2904, 'library': 2905, 'mr2': 2906, 'climb': 2907, 'cuddle': 2908, 'jilla': 2909, 'headline': 2910, '2017': 2911, 'jumma': 2912, 'mubarik': 2913, 'total': 2914, 'congratz': 2915, 'contribution': 2916, '2.0': 2917, 'yuppiieee': 2918, 'alienthought': 2919, 'happyalien': 2920, 'crowd': 2921, 'loud': 2922, 'gary': 2923, 'particular': 2924, 'attraction': 2925, 'supprt': 2926, 'savage': 2927, 'cleanse': 2928, 'scam': 2929, 'ridden': 2930, 'vyapam': 2931, 'rename': 2932, 'wave': 2933, 'couch': 2934, 'dodge': 2935, 'explanation': 2936, 'bag': 2937, 'sanza': 2938, 'yaa': 2939, 'slr': 2940, 'som': 2941, 'honour': 2942, 'hehehe': 2943, 'view': 2944, 'explorer': 2945, 'wayanadan': 2946, 'forest': 2947, 'wayanad': 2948, 'srijith': 2949, 'whisper': 2950, 'lie': 2951, 'pokemon': 2952, 'dazzle': 2953, 'urself': 2954, 'double': 2955, 'flare': 2956, 'black': 2957, '9': 2958, '51': 2959, 'browse': 2960, 'bore': 2961, 'female': 2962, 'tour': 2963, 'delve': 2964, 'muchhh': 2965, 'tmr': 2966, 'breakfast': 2967, 'gl': 2968, \"tonight's\": 2969, '):': 2970, 'litey': 2971, 'manuella': 2972, 'maine': 2973, 'abhi': 2974, 'tak': 2975, 'ye': 2976, 'nhi': 2977, 'dekhi': 2978, 'promos': 2979, 'se': 2980, 'welcomed': 2981, 'xpax': 2982, 'lisa': 2983, 'aboard': 2984, 'institution': 2985, 'nc': 2986, 'cheese': 2987, 'overload': 2988, 'pizza': 2989, '•': 2990, 'mcfloat': 2991, 'fudge': 2992, 'sandae': 2993, 'munchkins': 2994, \"d'd\": 2995, 'granny': 2996, 'baller': 2997, 'lil': 2998, 'chain': 2999, 'everybody': 3000, 'ought': 3001, 'jay': 3002, 'events@breastcancernow.org': 3003, '79x': 3004, 'champion': 3005, 'letter': 3006, 'approve': 3007, 'unique': 3008, 'affaraid': 3009, 'dearslim': 3010, 'role': 3011, 'billy': 3012, 'labs': 3013, 'ovh': 3014, 'maxi': 3015, 'bunch': 3016, 'acc': 3017, 'sprit': 3018, 'yous': 3019, 'til': 3020, 'severe': 3021, 'hammies': 3022, 'freedom': 3023, 'pistol': 3024, 'unlock': 3025, 'bemeapp': 3026, 'thumb': 3027, 'beme': 3028, 'bemecode': 3029, 'proudtobeme': 3030, 'round': 3031, 'calm': 3032, 'kepo': 3033, 'luckily': 3034, 'clearly': 3035, 'دعمم': 3036, 'للعودة': 3037, 'للحياة': 3038, 'heiyo': 3039, 'dudaftie': 3040, 'breaktym': 3041, 'fatal': 3042, 'dangerous': 3043, 'term': 3044, 'health': 3045, 'outraged': 3046, '645k': 3047, 'muna': 3048, 'magstart': 3049, 'salute': 3050, '→': 3051, 'thq': 3052, 'continous': 3053, 'thalaivar': 3054, '£': 3055, 'heiya': 3056, 'grab': 3057, '30.000': 3058, 'av': 3059, 'gd': 3060, 'wknd': 3061, 'ear': 3062, 'yesss': 3063, \"y'day\": 3064, 'hxh': 3065, 'besides': 3066, 'vids': 3067, 'badass': 3068, 'killua': 3069, 'scene': 3070, 'suffering': 3071, 'feed': 3072, '78x': 3073, 'unappreciated': 3074, 'gracious': 3075, 'nailedit': 3076, 'ourdisneyinfinity': 3077, 'mary': 3078, 'jillmill': 3079, 'webcam': 3080, 'elfindelmundo': 3081, 'sexi': 3082, 'mainly': 3083, 'favour': 3084, 'dancetastic': 3085, 'satyajit': 3086, \"ray's\": 3087, 'porosh': 3088, 'pathor': 3089, 'situation': 3090, 'goldbugs': 3091, 'wine': 3092, 'bottle': 3093, 'spill': 3094, 'jazmin': 3095, 'bonilla': 3096, '15000': 3097, 'star': 3098, 'hollywood': 3099, 'rofl': 3100, 'shade': 3101, 'grey': 3102, 'netsec': 3103, 'edition': 3104, 'ate': 3105, 'kev': 3106, 'apology': 3107, 'fangirled': 3108, 'sister': 3109, 'unlisted': 3110, 'hickey': 3111, 'dad': 3112, 'hock': 3113, 'mamma': 3114, 'human': 3115, 'being': 3116, 'mere': 3117, 'holistic': 3118, 'cosmovision': 3119, 'narrow-minded': 3120, 'charge': 3121, 'ce': 3122, 'alix': 3123, 'quan': 3124, 'tip': 3125, 'naaahhh': 3126, 'duh': 3127, 'emesh': 3128, 'hilarious': 3129, 'kath': 3130, 'kia': 3131, '@vauk': 3132, 'tango': 3133, 'tracerequest': 3134, 'homie': 3135, 'dassy': 3136, 'fwm': 3137, 'selamat': 3138, 'nichola': 3139, 'found': 3140, 'malta': 3141, 'gto': 3142, 'tomorrowland': 3143, 'incall': 3144, 'shobs': 3145, 'incomplete': 3146, 'barkada': 3147, 'silverstone': 3148, 'pull': 3149, 'bookstore': 3150, 'lately': 3151, 'ganna': 3152, 'hillary': 3153, 'clinton': 3154, 'court': 3155, 'notice': 3156, 'slice': 3157, 'life-so': 3158, 'hide': 3159, 'untapped': 3160, 'mca': 3161, 'gettin': 3162, 'hella': 3163, 'wana': 3164, 'bandz': 3165, 'hell': 3166, 'donington': 3167, 'park': 3168, '24/25': 3169, 'hop': 3170, 'x30': 3171, 'merci': 3172, 'bien': 3173, 'amie': 3174, 'pitbull': 3175, '777x': 3176, 'fri': 3177, 'annyeong': 3178, 'oppa': 3179, 'indonesian': 3180, 'elf': 3181, 'flight': 3182, 'bf': 3183, 'jennyjean': 3184, 'kikchat': 3185, 'sabadodeganarseguidores': 3186, 'sexysasunday': 3187, 'marseille': 3188, 'ganda': 3189, 'fnaf': 3190, 'steam': 3191, 'assure': 3192, 'current': 3193, 'goin': 3194, 'sweety': 3195, \"spot's\": 3196, 'barnstaple': 3197, 'bideford': 3198, 'abit': 3199, 'road': 3200, 'rocro': 3201, '13glodyysbro': 3202, 'hire': 3203, '2ne1': 3204, 'aspetti': 3205, 'chicken': 3206, 'chip': 3207, 'cupboard': 3208, 'empty': 3209, 'jamie': 3210, 'ian': 3211, 'latin': 3212, 'asian': 3213, 'version': 3214, 'fave': 3215, 'vaing': 3216, '642': 3217, 'kikgirl': 3218, 'orgasm': 3219, 'phonesex': 3220, 'spacers': 3221, 'felicity': 3222, 'smoak': 3223, '👓': 3224, '💘': 3225, 'child': 3226, 'psychopaths': 3227, 'spoile': 3228, 'dimple': 3229, 'contemplate': 3230, 'indie': 3231, 'route': 3232, 'jsl': 3233, '76x': 3234, 'gotcha': 3235, 'kina': 3236, 'donna': 3237, 'reachability': 3238, 'jk': 3239, 'bitter': 3240, 's02e04': 3241, 'air': 3242, 'naggy': 3243, 'anal': 3244, 'vidcon': 3245, 'anxious': 3246, 'shake': 3247, '10:30': 3248, 'smoke': 3249, 'white': 3250, 'grandpa': 3251, 'prolly': 3252, 'stash': 3253, 'closer-chasing': 3254, 'spec': 3255, 'league': 3256, 'chase': 3257, 'wall': 3258, 'angel': 3259, 'mochamichelle': 3260, 'iph': 3261, '0ne': 3262, 'simply': 3263, 'bi0': 3264, 'x29': 3265, 'there': 3266, 'background': 3267, 'maggie': 3268, 'afraid': 3269, 'mull': 3270, 'nil': 3271, 'glasgow': 3272, 'netball': 3273, 'thistle': 3274, 'thistlelove': 3275, 'effect': 3276, 'minecraft': 3277, 'boring': 3278, 'drew': 3279, 'delicious': 3280, 'muddle': 3281, 'racket': 3282, 'isolate': 3283, 'fa': 3284, 'participate': 3285, 'icecreammaster': 3286, 'group': 3287, 'huhu': 3288, 'shet': 3289, 'desk': 3290, 'o_o': 3291, 'orz': 3292, 'problemmm': 3293, '75x': 3294, 'english': 3295, 'yeeaayy': 3296, 'alhamdulillah': 3297, 'amin': 3298, 'weed': 3299, 'definition': 3300, 'crowdfunding': 3301, 'goal': 3302, 'walk': 3303, 'hellooo': 3304, 'selection': 3305, 'lynne': 3306, 'buffer': 3307, 'button': 3308, 'composer': 3309, 'fridayfun': 3310, 'non-filipina': 3311, 'ejayster': 3312, 'united': 3313, 'state': 3314, 'le': 3315, 'stan': 3316, 'lee': 3317, 'discovery': 3318, 'cousin': 3319, '1400': 3320, 'yrs': 3321, 'teleportation': 3322, 'shahid': 3323, 'afridi': 3324, 'tou': 3325, 'mahnor': 3326, 'baloch': 3327, 'nikki': 3328, 'flower': 3329, 'blackfly': 3330, 'courgette': 3331, 'wont': 3332, 'affect': 3333, 'fruit': 3334, 'italian': 3335, 'netfilx': 3336, 'unmarried': 3337, 'finger': 3338, 'rock': 3339, 'wiellys': 3340, 'paul': 3341, 'barcode': 3342, 'charlotte': 3343, 'thtas': 3344, 'trailblazerhonors': 3345, 'labour': 3346, 'leader': 3347, 'alot': 3348, 'agayhippiehippy': 3349, 'exercise': 3350, 'better': 3351, 'ginger': 3352, 'x28': 3353, 'teach': 3354, 'awareness': 3355, '::': 3356, 'portsmouth': 3357, 'sonal': 3358, 'hungry': 3359, 'hmmm': 3360, 'pedant': 3361, '98': 3362, 'kit': 3363, 'ack': 3364, 'hih': 3365, 'choir': 3366, 'rosidbinr': 3367, 'duke': 3368, 'earl': 3369, 'tau': 3370, 'awak': 3371, 'orayt': 3372, 'knw': 3373, 'block': 3374, 'dikha': 3375, 'reh': 3376, 'adolf': 3377, 'hitler': 3378, 'obstacle': 3379, 'exist': 3380, 'surrender': 3381, 'terrific': 3382, 'advaddict': 3383, '_15': 3384, 'jimin': 3385, 'notanapology': 3386, 'map': 3387, 'informed': 3388, '0.7': 3389, 'dependency': 3390, 'motherfucking': 3391, \"david's\": 3392, 'damn': 3393, 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3456, 'x27': 3457, 'dayz': 3458, 'preview': 3459, 'thug': 3460, 'lmao': 3461, 'sharethelove': 3462, 'highvalue': 3463, 'halsey': 3464, '30th': 3465, 'wed': 3466, 'anniversary': 3467, 'folk': 3468, 'bae': 3469, 'reply': 3470, 'complain': 3471, 'rude': 3472, 'bond': 3473, 'niggs': 3474, 'readingres': 3475, 'wordoftheweek': 3476, 'wotw': 3477, '4:18': 3478, 'est': 3479, 'earn': 3480, 'whatevs': 3481, 'jess': 3482, 'surry': 3483, 'botany': 3484, 'gel': 3485, 'alison': 3486, 'lsa': 3487, 'response': 3488, 'fron': 3489, 'debbie': 3490, 'carol': 3491, 'patient': 3492, 'discharge': 3493, 'lounge': 3494, 'walmart': 3495, 'balance': 3496, 'study': 3497, 'hayley': 3498, 'shoulder': 3499, 'pad': 3500, 'mount': 3501, 'inquisitor': 3502, 'cosplay': 3503, 'cosplayprogress': 3504, 'mike': 3505, 'dunno': 3506, 'housing': 3507, 'insecurity': 3508, 'nh': 3509, 'devolution': 3510, 'patriotism': 3511, 'halla': 3512, 'ark': 3513, \"jiyeon's\": 3514, 'buzz': 3515, 'burnt': 3516, 'mist': 3517, 'opi': 3518, 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'patiently': 5466, '😴': 5467, 'pglcsgo': 5468, 'x2': 5469, 'tend': 5470, 'crave': 5471, 'sjw': 5472, 'cakehamper': 5473, 'glow': 5474, 'yayyy': 5475, 'mercedes': 5476, 'hood': 5477, 'badge': 5478, 'hosted': 5479, 'drone': 5480, 'blow': 5481, 'ignore': 5482, 'retaliate': 5483, 'bollinger': 5484, \"where's\": 5485, 'planning': 5486, 'denmark': 5487, 'whitey': 5488, 'culture': 5489, 'coursee': 5490, 'intro': 5491, 'graphicdesign': 5492, 'videographer': 5493, 'youtuber': 5494, 'space': 5495, \"ted's\": 5496, 'bogus': 5497, '1000': 5498, 'hahahaaah': 5499, 'owly': 5500, 'afternon': 5501, 'whangarei': 5502, 'katie': 5503, 'nicholas': 5504, 'pauline': 5505, 'trafficker': 5506, 'daring': 5507, 'hence': 5508, 'expression': 5509, 'wot': 5510, 'hand-lettering': 5511, 'roof': 5512, 'ease': 5513, '2/2': 5514, 'sour': 5515, 'dough': 5516, 'egypt': 5517, 'hubby': 5518, 'mixed': 5519, 'sakin': 5520, 'six': 5521, 'christmas': 5522, 'avril': 5523, 'n04js': 5524, '25': 5525, 'prosecco': 5526, 'pech': 5527, 'micro': 5528, 'catspjs': 5529, '4:15': 5530, 'lazyweekend': 5531, 'overdue': 5532, '💃': 5533, 'jurassic': 5534, 'ding': 5535, 'nila': 5536, 'pairing': 5537, '8)': 5538, 'unfortunately': 5539, 'cookie': 5540, 'shir': 5541, '0': 5542, 'hale': 5543, 'cheshire': 5544, 'decorate': 5545, 'lemme': 5546, 'recs': 5547, 'ingat': 5548, 'din': 5549, 'mono': 5550, 'kathryn': 5551, 'jr': 5552, 'develop': 5553, 'hsr': 5554, 'base': 5555, 'major': 5556, 'sugarrush': 5557, 'knitting': 5558, 'partly': 5559, 'binge': 5560, 'homegirl': 5561, 'nancy': 5562, 'fenja': 5563, 'aapke': 5564, 'benchmark': 5565, 'ke': 5566, 'hisaab': 5567, 'ho': 5568, 'gaya': 5569, 'ofc': 5570, 'influence': 5571, 'rtss': 5572, 'hwaiting': 5573, 'titanfall': 5574, 'xbox': 5575, 'ultimate': 5576, 'experiment': 5577, 'gastronomy': 5578, 'newblogpost': 5579, 'foodiefridays': 5580, 'foodie': 5581, 'yoghurt': 5582, 'pancake': 5583, 'sabah': 5584, 'kapima': 5585, 'gelen': 5586, 'guzel': 5587, 'bir': 5588, 'hediye': 5589, 'thanx': 5590, '💞': 5591, 'visa': 5592, 'parisa': 5593, 'epiphany': 5594, 'lit': 5595, 'em-con': 5596, 'defender': 5597, '0330 333 7234': 5598, 'retailer': 5599, 'kianweareproud': 5600, 'distract': 5601, 'dayofarch': 5602, '10-20': 5603, 'bapu': 5604, 'ivypowel': 5605, 'newmusic': 5606, 'sexchat': 5607, '🍅': 5608, 'pathway': 5609, 'balkan': 5610, 'gypsy': 5611, 'mayhem': 5612, 'burek': 5613, 'meat': 5614, 'gibanica': 5615, 'pie': 5616, 'likely': 5617, 'surrey': 5618, 'afterwards': 5619, '10.30': 5620, 'heard': 5621, 'temporal': 5622, 'void': 5623, 'stem': 5624, 'sf': 5625, 'ykr': 5626, 'sparky': 5627, '40mm': 5628, '3.5': 5629, 'grs': 5630, 'rockfishing': 5631, 'topwater': 5632, 'twitlonger': 5633, 'me.so': 5634, 'jummah': 5635, 'durood': 5636, 'pak': 5637, 'cjradacomateada': 5638, 'suprised': 5639, 'debut': 5640, 'shipper': 5641, 'aside': 5642, 'housemate': 5643, '737bigatingconcert': 5644, 'jedzjabłka': 5645, 'pijjabłka': 5646, 'polish': 5647, 'cider': 5648, 'mustread': 5649, 'cricket': 5650, 'origin': 5651, '5pm': 5652, 'query': 5653, 'abby': 5654, 'sumedh': 5655, 'sunnah': 5656, 'عن': 5657, 'quad': 5658, 'bike': 5659, 'carrie': 5660, 'propriety': 5661, 'chronic': 5662, 'illness': 5663, 'superday': 5664, 'chocolatey': 5665, 'yasu': 5666, 'ooooh': 5667, 'fucked': 5668, 'hallo': 5669, 'improvement': 5670, 'dylan': 5671, 'laura': 5672, 'patrice': 5673, 'keepin': 5674, 'mohr': 5675, 'guest': 5676, \"o'neal\": 5677, 'tks': 5678, 'luas': 5679, 'stone': 5680, 'quicker': 5681, 'diet': 5682, 'sosweet': 5683, 'nominiere': 5684, 'und': 5685, 'hardcore': 5686, '😌': 5687, 'ff__special': 5688, 'acha': 5689, 'banda': 5690, '✌': 5691, 'bhi': 5692, 'krta': 5693, 'beautifully-crafted': 5694, 'mockingbird': 5695, 'diploma': 5696, 'blend': 5697, 'numbero': 5698, 'lolz': 5699, 'ambrose': 5700, 'gwinett': 5701, 'bierce': 5702, 'suffer': 5703, 'ravage': 5704, 'illadvised': 5705, 'marriage': 5706, 'virginity': 5707, 'cynical': 5708, 'yahuda': 5709, 'nosmet': 5710, 'pony': 5711, 'cuuute': 5712, \"f'ing\": 5713, 'vacant': 5714, 'hauc': 5715, 'hiss': 5716, 'overnight': 5717, 'cornish': 5718, 'all-clear': 5719, 'complains': 5720, 'raincoat': 5721, 'measure': 5722, 'wealth': 5723, 'invest': 5724, 'garbi': 5725, 'wash': 5726, 'refuel': 5727, 'dunedin': 5728, 'kalle': 5729, 'rakhi': 5730, 'photographer': 5731, '12th': 5732, 'carry': 5733, 'represent': 5734, 'slovenia': 5735, 'fridge': 5736, 'fighting': 5737, 'ludlow': 5738, '28th': 5739, 'selway': 5740, 'submit': 5741, 'spanish': 5742, 'greet': 5743, '90210': 5744, 'oitnb': 5745, 'prepare': 5746, 'condition': 5747, 'msged': 5748, 'chiquitos': 5749, 'ohaha': 5750, 'delhi': 5751, '95': 5752, 'webtogsawards': 5753, 'grace': 5754, 'sheffield': 5755, 'tramline': 5756, 'tl': 5757, 'hack': 5758, 'lad': 5759, 'beeepin': 5760, 'duper': 5761, 'handle': 5762, 'critique': 5763, 'contectually': 5764, 'beliebers': 5765, 'ultor': 5766, 'mamaya': 5767, 'loiyals': 5768, 'para': 5769, 'truthfulwordsof': 5770, 'beanatividad': 5771, 'nknkkpagpapakumbaba': 5772, 'birthdaypresent': 5773, 'compliment': 5774, 'swerve': 5775, 'goodtime': 5776, 'sinister': 5777, 'tryna': 5778, 'anonymous': 5779, 'dipsatch': 5780, 'aunt': 5781, 'dagga': 5782, 'burketeer': 5783, '2am': 5784, 'promo': 5785, 'required': 5786, 'twine': 5787, \"diane's\": 5788, 'happybirthday': 5789, 'thanksss': 5790, 'randomly': 5791, 'buckinghampalace': 5792, 'personality': 5793, 'chibi': 5794, 'maker': 5795, 'timog': 5796, '18th': 5797, 'otw': 5798, 'kami': 5799, 'feelinggood': 5800, 'demand': 5801, 'naman': 5802, 'barkin': 5803, 'yeap': 5804, 'onkey': 5805, 'umma': 5806, 'pervert': 5807, 'onyu': 5808, 'appa': 5809, 'lucy': 5810, 'horrible': 5811, 'quantum': 5812, 'blockchain': 5813, 'nowplaying': 5814, 'loftey': 5815, 'routte': 5816, 'assia': 5817, '.\\n.\\n.': 5818, 'joint': 5819, 'futurereleases': 5820, \"look's\": 5821, 'scary': 5822, 'murder': 5823, 'mystery': 5824, 'comma': 5825, \"j's\": 5826, 'hunny': 5827, 'diva': 5828, 'emily': 5829, 'nathan': 5830, 'meditation': 5831, 'alumnus': 5832, 'mba': 5833, 'representative': 5834, 'foto': 5835, 'what-is-your-fashionality': 5836, 'lorenangel': 5837, 'kw': 5838, 'tellanoldjokeday': 5839, 'reqd': 5840, 'speculation': 5841, 'consistency': 5842, 'tropic': 5843, 'startupph': 5844, 'zodiac': 5845, 'rapunzel': 5846, 'imaginative': 5847, 'therver': 5848, '85552': 5849, 'bestoftheday': 5850, 'oralsex': 5851, 'carly': 5852, 'happily': 5853, 'contract': 5854, 'matsu_bouzu': 5855, 'sonic': 5856, 'videogames': 5857, 'harana': 5858, 'belfast': 5859, 'danny': 5860, 'rare': 5861, 'sponsorship': 5862, 'aswell': 5863, 'gigi': 5864, 'nick': 5865, 'austin': 5866, 'youll': 5867, 'weak': 5868, '10,000': 5869, 'bravo': 5870, 'iamamonster': 5871, 'rxthedailysurveyvotes': 5872, 'as': 5873, 'roux': 5874, 'walkin': 5875, 'audience': 5876, 'pfb': 5877, 'jute': 5878, 'walangmakakapigilsakin': 5879, 'lori': 5880, 'ehm': 5881, 'trick': 5882, 'baekhyun': 5883, 'eyesmiles': 5884, 'borrow': 5885, 'knife': 5886, 'thek': 5887, 'widely': 5888, 'eventually': 5889, 'reaapearing': 5890, 'kno': 5891, 'whet': 5892, 'grattis': 5893, 'tweetin': 5894, 'inshallah': 5895, 'banana': 5896, 'raspberry': 5897, 'healthylifestyle': 5898, 'aint': 5899, 'skate': 5900, 'analyze': 5901, 'variety': 5902, 'twitching': 5903, '4:13': 5904, 'insomnia': 5905, 'medication': 5906, 'opposite': 5907, 'everlasting': 5908, 'yoga': 5909, 'massage': 5910, 'osteopath': 5911, 'trainer': 5912, 'sharm': 5913, 'al_master_band': 5914, 'tbc': 5915, 'univesity': 5916, 'architecture': 5917, 'random': 5918, 'isnt': 5919, 'typo': 5920, 'snark': 5921, 'lessions': 5922, 'drunk': 5923, 'bruuh': 5924, '2weeks': 5925, '50europe': 5926, '🇫🇷': 5927, 'iove': 5928, 'accord': 5929, 'mne': 5930, 'pchelok': 5931, 'ja': 5932, 'carefully': 5933, '=:': 5934, 'comet': 5935, 'ahah': 5936, 'candy': 5937, 'axio': 5938, 'remind': 5939, 'rabbit': 5940, 'nutshell': 5941, 'letshavecocktailsafternuclai': 5942, 'malik': 5943, 'umair': 5944, 'celebrity': 5945, 'canon': 5946, 'gang': 5947, 'grind': 5948, 'thoracicbridge': 5949, '5minute': 5950, 'nonscripted': 5951, 'password': 5952, 'shoshannavassil': 5953, 'addmeonsnapchat': 5954, 'dmme': 5955, 'mpoints': 5956, 'soph': 5957, 'subjective': 5958, 'painful': 5959, 'hopeless': 5960, 'ikea': 5961, 'slide': 5962, 'ban': 5963, 'neighbour': 5964, 'motor': 5965, 'search': 5966, 'sialan': 5967, 'athabasca': 5968, 'glacier': 5969, '1948': 5970, ':-(': 5971, 'jasper': 5972, 'jaspernationalpark': 5973, 'alberta': 5974, 'explorealberta': 5975, 'mare': 5976, 'ivan': 5977, 'hahahah': 5978, 'replacement': 5979, 'bi-polar': 5980, 'grasp': 5981, 'basic': 5982, 'digital': 5983, 'research': 5984, '😩': 5985, 'choreographing': 5986, 'longer': 5987, 'mingming': 5988, 'truly': 5989, 'pee': 5990, 'newwine': 5991, 'doushite': 5992, 'gundam': 5993, 'dollar': 5994, 'pale': 5995, 'imitation': 5996, 'rash': 5997, 'absent': 5998, 'sequel': 5999, 'ouucchhh': 6000, 'wisdom': 6001, 'teeth': 6002, 'frighten': 6003, 'pret': 6004, 'wkwkw': 6005, 'verfied': 6006, 'sentir-se': 6007, 'incompleta': 6008, 'thwarting': 6009, 'zante': 6010, \"when's\": 6011, 'audraesar': 6012, 'craaazzyy': 6013, 'helium': 6014, 'climatechange': 6015, \"california's\": 6016, 'influential': 6017, 'pollution': 6018, 'watchdog': 6019, 'califor': 6020, 'elhaida': 6021, 'jury': 6022, '10th': 6023, 'televoting': 6024, 'idaho': 6025, 'drought-linked': 6026, 'die-of': 6027, 'abrupt': 6028, 'climate': 6029, 'mammoth': 6030, 'megafauna': 6031, \"australia's\": 6032, 'considers': 6033, 'energy': 6034, 'biomass': 6035, 'golf': 6036, 'ulti': 6037, 'prexy': 6038, 'kindergarten': 6039, 'sane': 6040, 'boss': 6041, 'hozier': 6042, 'soooner': 6043, 'respectlost': 6044, 'hypercholesteloremia': 6045, 'calibraska': 6046, 'genuine': 6047, 'contender': 6048, 'aos': 6049, 'yun': 6050, 'encore': 6051, '4thwin': 6052, 'baymax': 6053, 'mixer': 6054, 'wft': 6055, 'promotion': 6056, 'hub': 6057, 'finale': 6058, 'parasyte': 6059, 'alll': 6060, 'zayniscomingbackonjuly': 6061, '26': 6062, 'era': 6063, '。': 6064, 'ω': 6065, '」': 6066, '∠': 6067, 'nathann': 6068, 'dieididieieiei': 6069, 'netflix': 6070, 'ervin': 6071, 'accept': 6072, 'desperate': 6073, 'amargolonnard': 6074, 'batalladelosgallos': 6075, 'webcamsex': 6076, 'duty': 6077, \"u've\": 6078, 'alien': 6079, 'sorka': 6080, 'funeral': 6081, 'nonexistent': 6082, 'wowza': 6083, 'fah': 6084, 'boo': 6085, 'hyung': 6086, 'predict': 6087, 'sj': 6088, 'nominate': 6089, 'brace': 6090, 'omggg': 6091, 'whyyy': 6092, 'annoying': 6093, 'evan': 6094, 'opt': 6095, 'muster': 6096, 'merchs': 6097, 'drinking': 6098, 'savanna': 6099, 'straw': 6100, 'yester': 6101, 'whens': 6102, 'consume': 6103, 'werk': 6104, 'foreals': 6105, 'wesen': 6106, 'uwesiti': 6107, 'bosen': 6108, 'egg': 6109, 'benny': 6110, 'badly': 6111, '>:(': 6112, 'zaz': 6113, 'rehash': 6114, 'mushroom': 6115, 'piece': 6116, 'exception': 6117, 'vicky': 6118, '45': 6119, 'hahah': 6120, 'ninasty': 6121, 'tsktsk': 6122, 'dick': 6123, 'kawaii': 6124, 'manly': 6125, 'youu': 6126, 'potato': 6127, 'fry': 6128, 'asf': 6129, 'eish': 6130, 'ive': 6131, 'mojo': 6132, 'mara': 6133, 'neh': 6134, 'association': 6135, 'councillor': 6136, 'sholong': 6137, 'reject': 6138, 'gee': 6139, 'gidi': 6140, 'lagos': 6141, 'ehn': 6142, 'arrest': 6143, 'idk': 6144, 'anybody': 6145, 'disappear': 6146, 'daze': 6147, 'fragment': 6148, \"would've\": 6149, 'walao': 6150, 'kbs': 6151, 'djderek': 6152, 'legend': 6153, 'tragedy': 6154, '💪🏻': 6155, '🐒': 6156, 'strucked': 6157, 'belgium': 6158, 'fabian': 6159, 'delph': 6160, 'draking': 6161, 'silently': 6162, 'mumma': 6163, 'pray': 6164, 'appropriate': 6165, 'woke': 6166, 'across': 6167, 'hindi': 6168, 'disability': 6169, 'pension': 6170, 'ptsd': 6171, 'impossible': 6172, 'physically': 6173, 'financially': 6174, 'nooo': 6175, 'togheter': 6176, '21st': 6177, 'snsd': 6178, 'anna': 6179, 'akana': 6180, 'askip': 6181, \"t'existes\": 6182, 'decides': 6183, 'kei': 6184, 'kate': 6185, 'spade': 6186, 'pero': 6187, 'walang': 6188, 'agesss': 6189, 'corinehurleigh': 6190, 'snapchatme': 6191, 'sfs': 6192, 'zara': 6193, 'trouser': 6194, \"it'okay\": 6195, 'luckely': 6196, 'orcalove': 6197, 'lew': 6198, 'crumble': 6199, 'mcflurry': 6200, 'cable': 6201, 'scared': 6202, \"venus's\": 6203, 'concept': 6204, 'rly': 6205, 'tagal': 6206, 'awful': 6207, 'appointment': 6208, 'cereal': 6209, 'previous': 6210, '73': 6211, 'fansign': 6212, 'expensive': 6213, 'zzzz': 6214, \"bff's\": 6215, 'extremely': 6216, \"deosn't\": 6217, 'liverpool': 6218, 'tacky': 6219, 'haaretz': 6220, 'israel': 6221, 'syria': 6222, 'chemical': 6223, 'wsj': 6224, 'rep': 6225, 'bts': 6226, 'wong': 6227, 'confiscate': 6228, 'icepack': 6229, 'dos': 6230, 'whimper': 6231, 'senpai': 6232, 'buttsex': 6233, \"dn't\": 6234, 'brk': 6235, \":'(\": 6236, 'falsetto': 6237, 'zone': 6238, 'loveofmylife': 6239, 's2': 6240, 'untruth': 6241, 'ij': 6242, '💥': 6243, '💫': 6244, 'soshi': 6245, 'buttt': 6246, 'heyyy': 6247, 'yeols': 6248, 'danceee': 6249, 'nemanja': 6250, 'vidic': 6251, 'roma': 6252, \"mom's\": 6253, 'linguist': 6254, \"dad's\": 6255, 'dumb': 6256, 'wanted': 6257, 'pouring': 6258, 'crash': 6259, 'resource': 6260, 'vehicle': 6261, 'ayex': 6262, 'lamon': 6263, 'scroll': 6264, 'curve': 6265, 'cement': 6266, '10.3': 6267, 'jmu': 6268, 'camp': 6269, 'tease': 6270, 'awuna': 6271, 'mbulelo': 6272, 'although': 6273, 'crackling': 6274, 'plug': 6275, 'fuse': 6276, 'dammit': 6277, 'carlton': 6278, 'aflblueshawks': 6279, \"alex's\": 6280, 'motorsport': 6281, 'cheeky': 6282, 'seo': 6283, 'nls': 6284, 'christy': 6285, 'niece': 6286, 'bloody': 6287, 'sandwhich': 6288, 'buset': 6289, 'discrimination': 6290, 'pregnancy': 6291, 'maternity': 6292, 'kick': 6293, 'domesticviolence': 6294, 'domestic': 6295, 'violence': 6296, 'victim': 6297, '98fm': 6298, 'stressful': 6299, 'upsetting': 6300, 'government': 6301, 'sapiosexual': 6302, 'beta': 6303, 'hogan': 6304, 'scrub': 6305, 'wwe': 6306, 'irene': 6307, 'naa': 6308, 'h_my_king': 6309, 'valentine': 6310, 'et': 6311, \"r'ships\": 6312, 'btwn': 6313, 'homo': 6314, 'biphobic': 6315, 'discipline': 6316, 'incl': 6317, 'european': 6318, 'langs': 6319, 'fresherstofinals': 6320, '💔': 6321, 'realistic': 6322, 'liking': 6323, 'prefer': 6324, 'benzema': 6325, 'hahahahahaah': 6326, 'donno': 6327, 'russian': 6328, 'waaa': 6329, 'eidwithgrofers': 6330, 'boreddd': 6331, 'mug': 6332, 'tiddler': 6333, '에이핑크': 6334, '더쇼': 6335, 'clan': 6336, 'slot': 6337, 'pfff': 6338, 'bugbounty': 6339, 'self-xss': 6340, 'host': 6341, 'header': 6342, 'poison': 6343, 'execution': 6344, 'ktksbye': 6345, 'cancel': 6346, 'petite': 6347, '600': 6348, 'security': 6349, 'odoo': 6350, 'partner': 6351, 'effin': 6352, 'ap': 6353, 'living': 6354, 'elsewhere': 6355, 'branch': 6356, 'concern': 6357, 'pod': 6358, 'D;': 6359, 'talk-kama': 6360, 'hawako': 6361, 'waa': 6362, 'kimaaani': 6363, 'prisss': 6364, 'baggage': 6365, 'sugar': 6366, 'rarely': 6367, 'agh': 6368, 'undercoverboss': 6369, 'تكفى': 6370, 'ache': 6371, 'wrist': 6372, 'ligo': 6373, 'dozen': 6374, 'shark': 6375, 'heartache': 6376, 'zayniscomingback': 6377, 'sweden': 6378, 'elmhurst': 6379, 'etid': 6380, \"chillin'with\": 6381, 'father': 6382, 'istanya': 6383, '2supply': 6384, 'infrastructure': 6385, 'nurse': 6386, 'paramedic': 6387, 'countless': 6388, '2cope': 6389, 'bored': 6390, 'plea': 6391, 'arianator': 6392, 'streaming': 6393, 'kendall': 6394, 'kylie': 6395, \"kylie's\": 6396, 'manila': 6397, 'jeebus': 6398, 'reabsorbtion': 6399, 'abscess': 6400, 'threaten': 6401, 'crown': 6402, 'ooouch': 6403, 'barney': 6404, \"be's\": 6405, 'problematic': 6406, 'mess': 6407, 'maa': 6408, 'bangalore': 6409, 'luis': 6410, 'manzano': 6411, 'shaaa': 6412, 'convener': 6413, '2:30': 6414, 'delete': 6415, 'airfields': 6416, 'jet': 6417, \"jack's\": 6418, 'spamming': 6419, \"mommy's\": 6420, 'overweight': 6421, 'sigeg': 6422, 'habhab': 6423, 'masud': 6424, 'kaha': 6425, 'akong': 6426, 'pala': 6427, 'dolphin': 6428, 'holy': 6429, 'anythin': 6430, 'beware': 6431, 'agonising': 6432, 'modimo': 6433, 'tseba': 6434, 'wena': 6435, 'fela': 6436, 'nowt': 6437, 'willy': 6438, 'gon': 6439, 'vomit': 6440, 'bowl': 6441, 'devastate': 6442, 'titan': 6443, 'ae': 6444, 'shiny': 6445, 'wavy': 6446, 'emo': 6447, 'germany': 6448, 'shedding': 6449, 'bheyps': 6450, 'ayemso': 6451, 'left': 6452, 'swell': 6453, 'wut': 6454, 'vicious': 6455, 'simpson': 6456, 'singapore': 6457, 'pooo': 6458, 'bh3s': 6459, 'pitchwars': 6460, 'chap': 6461, \"mine's\": 6462, 'transcript': 6463, \"apma's\": 6464, 'timw': 6465, 'accs': 6466, 'vitamin': 6467, 'stretch': 6468, 'blockjam': 6469, \"schedule's\": 6470, 'whack': 6471, 'thelock': 6472, '76': 6473, 'hotgirls': 6474, 'ghantay': 6475, 'nai': 6476, 'hay': 6477, 'rejection': 6478, 'deny': 6479, 'laguna': 6480, 'exit': 6481, 'gomen': 6482, 'inch': 6483, 'suuuper': 6484, '65': 6485, 'anyones': 6486, 'inactive': 6487, 'orphan': 6488, 'whaaat': 6489, 'kaya': 6490, 'naaan': 6491, 'pause': 6492, '3:30': 6493, 'inglewood': 6494, 'ummm': 6495, 'charcoal': 6496, 'mid-end': 6497, 'noooo': 6498, 'rodfanta': 6499, 'wasp': 6500, 'sting': 6501, 'avert': 6502, 'exo': 6503, 'seekly': 6504, 'riptito': 6505, 'manbearpig': 6506, 'shorter': 6507, 'academic': 6508, 'exclusive': 6509, 'unfair': 6510, 'esp': 6511, 'bleak': 6512, 'german': 6513, 'chart': 6514, 'pfft': 6515, 'washed': 6516, 'polaroid': 6517, 'newbethvideo': 6518, 'greece': 6519, 'xur': 6520, 'imy': 6521, 'stud': 6522, 'earring': 6523, 'hunde': 6524, '3.4': 6525, 'yach': 6526, 'huvvft': 6527, 'zoo': 6528, 'fieldtrips': 6529, 'sizwe': 6530, 'boredom': 6531, 'who': 6532, 'sinse': 6533, 'somehow': 6534, 'tiny': 6535, 'barbell': 6536, 'looong': 6537, 'apartement': 6538, 'longe': 6539, 'litro': 6540, 'shepherd': 6541, 'lami': 6542, 'lungomare': 6543, 'pesaro': 6544, 'giachietittiwedding': 6545, 'igersoftheday': 6546, 'summertime': 6547, 'nose': 6548, 'scarf': 6549, 'aus': 6550, 'afford': 6551, 'woe': 6552, 'nigga': 6553, 'motn': 6554, 'lighting': 6555, 'make-up': 6556, 'limited': 6557, 'ver': 6558, 'huhuhu': 6559, \"m'lady\": 6560, 'j8': 6561, 'j11': 6562, 'm20': 6563, 'acads': 6564, 'schedule': 6565, 'nowww': 6566, 'hugh': 6567, 'paw': 6568, 'muddy': 6569, 'distracted': 6570, 'heyy': 6571, 'cupcake': 6572, 'talaga': 6573, 'poppin': 6574, 'joc': 6575, 'playin': 6576, 'subj': 6577, 'sobrang': 6578, 'bv': 6579, 'zamn': 6580, 'afropunk': 6581, 'fest': 6582, 'shithouse': 6583, 'ladder': 6584, 'wrack': 6585, 'booset': 6586, 'restart': 6587, 'assassin': 6588, 'creed': 6589, 'ii': 6590, 'heap': 6591, 'ankle': 6592, 'puddle': 6593, 'wearing': 6594, 'slipper': 6595, 'eve': 6596, 'sararocs': 6597, 'anywayhedidanicejob': 6598, '😞': 6599, 'local': 6600, 'cruise': 6601, 'wail': 6602, 'wheelchair': 6603, '26weeks': 6604, 'sbenu': 6605, 'sasin': 6606, 'anarchy': 6607, 'candle': 6608, 'forehead': 6609, 'medicine': 6610, 'hoya': 6611, 'mah': 6612, 'aing': 6613, 'hush': 6614, 'gurly': 6615, 'purty': 6616, 'closer': 6617, 'shiver': 6618, 'properly': 6619, 'gol': 6620, 'pea': 6621, 'emotionally': 6622, 'mentally': 6623, 'tierd': 6624, \"eye's\": 6625, 'thnkyouuu': 6626, 'highlight': 6627, 'courage': 6628, 'fishy': 6629, 'idek': 6630, 'apink': 6631, 'performance': 6632, 'bulet': 6633, 'gendut': 6634, 'noo': 6635, 'hotwheels': 6636, 'm': 6637, 'patch': 6638, 'ahaha': 6639, 'akon': 6640, 'nightmare': 6641, 'mino': 6642, 'crazyyy': 6643, 'thooo': 6644, 'zz': 6645, 'straight': 6646, 'soundcheck': 6647, 'antagonistic': 6648, 'ob': 6649, 'phantasy': 6650, 'sleepdeprived': 6651, 'tiredashell': 6652, '4aspot': 6653, \"kinara's\": 6654, 'awami': 6655, 'niqqa': 6656, 'pb.contestants': 6657, 'aarww': 6658, 'lmbo': 6659, 'dangit': 6660, 'ohmygod': 6661, 'scenario': 6662, 'tooo': 6663, 'baechyyy': 6664, 'okayyy': 6665, 'noone': 6666, 'drag': 6667, 'seriously': 6668, 'misundersranding': 6669, 'chal': 6670, 'raha': 6671, 'yhm': 6672, 'edsa': 6673, 'jasmingarrick': 6674, 'milf': 6675, 'nakamaforever': 6676, 'kiksex': 6677, 'tried': 6678, \"unicef's\": 6679, 'fu': 6680, 'alone': 6681, 'manage': 6682, 'stephen': 6683, 'frustration': 6684, 'sent': 6685, 'woza': 6686, 'senight': 6687, '468': 6688, 'amateur': 6689, 'hotscratch': 6690, 'sock': 6691, '150-160': 6692, 'peso': 6693, 'degrassi': 6694, 'bcz': 6695, 'kat': 6696, 'chem': 6697, 'onscreen': 6698, 'ofscreen': 6699, 'irony': 6700, 'rhisfor': 6701, 'camsex': 6702, 'poopie': 6703, 'pip': 6704, 'uff': 6705, '1.300': 6706, 'glue': 6707, 'factory': 6708, 'kuchar': 6709, 'ups': 6710, 'definite': 6711, 'uni': 6712, 'anyways': 6713, 'ee': 6714, 'tommy': 6715, 'georgia': 6716, 'transmission': 6717, 'orang': 6718, 'suma': 6719, 'shouldeeerr': 6720, 'repack': 6721, 'repacks': 6722, 'dye': 6723, 'rihanna': 6724, 'ginge': 6725, 'adidas': 6726, 'pro@illamasqua.com': 6727, 'ifeelyou': 6728, 'ratbaglater': 6729, 'semester': 6730, 'gin': 6731, 'gutted': 6732, 'reynold': 6733, 'dessert': 6734, 'village': 6735, 'unite': 6736, 'oppressed': 6737, 'mass': 6738, 'afghanistn': 6739, 'war': 6740, 'sunggyu': 6741, 'injure': 6742, 'plaster': 6743, 'rtd': 6744, 'stadium': 6745, 'welder': 6746, 'hogo': 6747, 'vishaya': 6748, 'adu': 6749, 'bjp': 6750, 'madatte': 6751, 'anta': 6752, 'vishwas': 6753, 'ne': 6754, 'illa': 6755, 'wua': 6756, 'noticed': 6757, 'picky': 6758, 'mutuals': 6759, 'unfollowed': 6760, 'thenting': 6761, '423': 6762, 'sexual': 6763, 'sync': 6764, 'plug.dj': 6765, 'suspemsion': 6766, 'cope': 6767, 'offroading': 6768, 'theres': 6769, 'harvest': 6770, 'machinery': 6771, 'inapropriate': 6772, 'weave': 6773, 'investment': 6774, 'scottish': 6775, 'football': 6776, 'dire': 6777, 'nomoney': 6778, 'nawf': 6779, 'bechos': 6780, 'overly': 6781, 'lab': 6782, 'zap': 6783, 'distressing': 6784, 'cinema': 6785, 'louisianashooting': 6786, 'laughing': 6787, 'har': 6788, 'chum': 6789, 'ncc': 6790, 'ph': 6791, 'kayo': 6792, 'itong': 6793, 'thaaat': 6794, 'ctto': 6795, 'expire': 6796, 'bis': 6797, 'broke': 6798, 'bi': 6799, '3:33': 6800, 'jfc': 6801, 'bodo': 6802, 'amat': 6803, 'yelaaa': 6804, 'dublin': 6805, 'potter': 6806, 'pining': 6807, 'keybind': 6808, 'warfare': 6809, 'controlls': 6810, 'diagnose': 6811, 'wiv': 6812, \"scheuermann's\": 6813, 'disease': 6814, 'rlyhurts': 6815, 'howdo': 6816, 'georgesampson': 6817, 'signal': 6818, 'reckon': 6819, 't20': 6820, 'taunton': 6821, 'hopeful': 6822, 'justiceforsandrabland': 6823, 'sandrabland': 6824, 'disturb': 6825, 'happpy': 6826, 'justinbieber': 6827, 'daianerufato': 6828, 'ilysm': 6829, '07:34': 6830, 'delphy': 6831, 'dom': 6832, 'technique': 6833, 'mince': 6834, 'symphony': 6835, 'joe': 6836, 'wth': 6837, 'aisyhhh': 6838, 'bald': 6839, 'seungchan': 6840, 'aigooo': 6841, 'riri': 6842, 'vet': 6843, 'va': 6844, 'luminous': 6845, 'km': 6846, 'horribly': 6847, 'z': 6848, 'popularity': 6849, 'bebeee': 6850, 'lt': 6851, 'inaccuracy': 6852, 'inaccurate': 6853, 'worried': 6854, 'tragic': 6855, 'toronto': 6856, 'stuart': 6857, \"party's\": 6858, 'iyalaya': 6859, ';(': 6860, 'ubusy': 6861, 'gymnastics': 6862, 'aahhh': 6863, 'noggin': 6864, 'bump': 6865, 'feelslikeanidiot': 6866, 'pregnant': 6867, 'dearly': 6868, 'suk': 6869, 'scone': 6870, 'outnumber': 6871, 'eris': 6872, 'geez': 6873, 'precious': 6874, 'hive': 6875, 'voting': 6876, 'vietnam': 6877, 'dunt': 6878, 'sob': 6879, 'buff': 6880, 'toni': 6881, 'deactivate': 6882, \"shady's\": 6883, 'isibaya': 6884, '😓': 6885, 'colder': 6886, 'med': 6887, 'sausage': 6888, 'adios': 6889, 'h8': 6890, 'messenger': 6891, 'shittier': 6892, 'leno': 6893, 'identity': 6894, 'crisis': 6895, 'roommate': 6896, 'nighter': 6897, 'wetherspoons': 6898, 'pubs': 6899, 'police': 6900, 'ocean': 6901, 'lisaherring': 6902, 'ebony': 6903, 'polka': 6904, 'ndi': 6905, 'leftover': 6906, 'walnut': 6907, 'boah': 6908, 'mady': 6909, 'manga': 6910, 'giant': 6911, 'aminormalyet': 6912, 'poorly': 6913, 'tummy': 6914, 'pjs': 6915, 'groaning': 6916, 'nou': 6917, 'ken': 6918, 'saras': 6919, 'accident': 6920, 'freaking': 6921, 'describe': 6922, 'prydz': 6923, 'sister-in-law': 6924, 'instal': 6925, 'rear-ended': 6926, \"everyone's\": 6927, 'trash': 6928, 'boobs': 6929, 'stair': 6930, 'childhood': 6931, 'toothsensitivity': 6932, 'shem': 6933, 'awell': 6934, 'weekendofmadness': 6935, '🍹': 6936, 'cb': 6937, 'dancer': 6938, 'choregrapher': 6939, '626-430-8715': 6940, 'replied': 6941, 'hoe': 6942, 'xiu': 6943, 'nk': 6944, 'gi': 6945, 'us': 6946, 'elisse': 6947, 'ksoo': 6948, 'tat': 6949, 'bcoz': 6950, 'rancho': 6951, 'imperial': 6952, 'silang': 6953, 'subdivision': 6954, 'center': 6955, '39': 6956, 'cornwall': 6957, 'veritably': 6958, 'penny': 6959, 'ebook': 6960, 'фотосет': 6961, 'addicted-to-analsex': 6962, 'sweetbj': 6963, 'blowjob': 6964, 'mhhh': 6965, 'sed': 6966, 'mee': 6967, 'envious': 6968, 'eonni': 6969, 'lovey': 6970, 'dovey': 6971, 'workin': 6972, 'schade': 6973, 'isco': 6974, 'penis': 6975, 'nation': 6976, 'louisiana': 6977, 'lafayette': 6978, 'matteroftheheart': 6979, 'waduh': 6980, 'suspend': 6981, 'smoking': 6982, 'cliche': 6983, 'rma': 6984, 'jersey': 6985, 'texted': 6986, 'jaclintiler': 6987, 'teens': 6988, 'likeforlike': 6989, 'hotfmnoaidilforariana': 6990, 'fuckkk': 6991, 'sanum': 6992, 'llaollao': 6993, 'foood': 6994, 'ubericecream': 6995, 'glare': 6996, 'choreo': 6997, 'offensive': 6998, 'yeyy': 6999, 'hd': 7000, 'sux': 7001, 'nothaveld': 7002, '765': 7003, 'likeforfollow': 7004, 'mosquitoe': 7005, 'kinky': 7006, 'hsould': 7007, 'justget': 7008, 'married': 7009, 'shuffle': 7010, 'inte': 7011, 'buckling': 7012, 'millz': 7013, 'askies': 7014, 'awusasho': 7015, 'unlucky': 7016, 'briefly': 7017, 'greatful': 7018, '144p': 7019, 'brooke': 7020, 'cracked': 7021, '＠': 7022, 'maverickgamer': 7023, '07:32': 7024, '07:25': 7025, 'external': 7026, 'sd': 7027, 'airdroid': 7028, '4.4+': 7029, 'cramp': 7030, 'unstan': 7031, 'tay': 7032, 'ngeze': 7033, 'cocktaily': 7034, 'classy': 7035, '07:24': 7036, '✈': 7037, '️2': 7038, '☔': 7039, 'pen': 7040, 'spar': 7041, 'barcelona': 7042, 'bilbao': 7043, 'sharyl': 7044, 'shane': 7045, 'giddy': 7046, 'd1': 7047, 'zipper': 7048, 'repair': 7049, '2016': 7050, 'cont': 7051, 'wore': 7052, 'tempt': 7053, 'oreo': 7054, 'network': 7055, 'lolipop': 7056, 'kebab': 7057, 'klappertart': 7058, 'moodboster': 7059, 'unprepared': 7060, 'sry': 7061, 'dresscode': 7062, 'closed': 7063, 'iam': 7064, 'stab': 7065, 'meh': 7066, 'wrocilam': 7067, 'looww': 7068, 'recover': 7069, 'wayne': 7070, 'loss': 7071, 'steal': 7072, 'accidentally': 7073, 'damage': 7074, 'device': 7075, 'warranty': 7076, 'lmfaoo': 7077, 'fra': 7078, 'otamendi': 7079, 'ny': 7080, '🚖': 7081, '🗽': 7082, '🌃': 7083, 'stealth': 7084, 'bastard': 7085, 'therapy': 7086, 'exhausting': 7087, 'understandable': 7088, 'switzerland': 7089, 'th': 7090, 'wolrd': 7091, 'fyn': 7092, 'genuinely': 7093, '3g': 7094, 'christ': 7095, 'scale': 7096, 'deck': 7097, 'chair': 7098, 'yk': 7099, 'resy': 7100, 'bruh': 7101, 'lock': 7102, 'fbc': 7103, 'mork': 7104, '873': 7105, 'hotspotwithdanris': 7106, 'sone': 7107, 'produce': 7108, 'potager': 7109, 'blight': 7110, 'mych': 7111, 'shiiit': 7112, 'prompt': 7113, 'aready': 7114, 'similar': 7115, 'soulmate': 7116, 'careful': 7117, 'hws': 7118, 'jouch': 7119, 'por': 7120, 'que': 7121, 'liceooo': 7122, 'ayala': 7123, 'tunnel': 7124, 'thatscold': 7125, 'lourdes': 7126, 'bang': 7127, 'anywhere': 7128, 'showbox': 7129, 'naruto': 7130, 'companion': 7131, 'skinny': 7132, 'dubai': 7133, 'laribuggy': 7134, 'nutella': 7135, \"could've\": 7136, 'sirius': 7137, 'frudging': 7138, 'bbz': 7139, 'angeke': 7140, 'sbali': 7141, 'euuuwww': 7142, 'construction': 7143, '1k': 7144, 'nelle': 7145, 'ik': 7146, 'jaysus': 7147, 'buti': 7148, 'poop': 7149, 'rome': 7150, 'throat': 7151, 'llama': 7152, 'getwellsoonamber': 7153, 'heath': 7154, 'ledger': 7155, 'permission': 7156, '2-0': 7157, 'supersport': 7158, 'milkshake': 7159, 'witcher': 7160, 'papertown': 7161, 'bale': 7162, 'bahay': 7163, 'bahayan': 7164, 'magisa': 7165, 'lang': 7166, 'sadlyf': 7167, 'bunso': 7168, 'sleeep': 7169, 'astonvilla': 7170, 'berigaud': 7171, 'bakar': 7172, 'allergic': 7173, 'depress': 7174, \"blaine's\": 7175, 'acoustic': 7176, 'hernia': 7177, 'toxin': 7178, 'ariel': 7179, 'slam': 7180, 'bee': 7181, 'finddjderek': 7182, 'uuughhh': 7183, 'grabe': 7184, 'wheres': 7185, 'smi': 7186, 'nemesis': 7187, 'neeein': 7188, 'saaad': 7189, 'crease': 7190, 'tanned': 7191, 'dallas': 7192, 'infront': 7193, 'beato': 7194, 'tim': 7195, 'minha': 7196, 'deleicious': 7197, 'pcb': 7198, 'got': 7199, 'peregrine': 7200, '8.40': 7201, 'pigeon': 7202, 'flew': 7203, 'tram': 7204, 'hav': 7205, 'spent': 7206, 'apt': 7207, 'bldg': 7208, 'mmmm': 7209, 'nicki': 7210, 'fucjikg': 7211, 'disgust': 7212, 'buynotanapologyonitunes': 7213, 'avalible': 7214, 'frustrate': 7215, 'nw': 7216, 'sch': 7217, 'jeslyn': 7218, '72': 7219, 'root': 7220, 'kuch': 7221, 'hua': 7222, 'newbie': 7223, 'miracle': 7224, 'linda': 7225, 'nux': 7226, 'hinanap': 7227, 'uy': 7228, 'sched': 7229, 'anyare': 7230, 'entertain': 7231, 'typa': 7232, 'transparency': 7233, 'photoshop': 7234, 'planner': 7235, 'helppp': 7236, 'wearig': 7237, 'dri': 7238, 'prey': 7239, 'ausfailia': 7240, 'snow': 7241, 'footy': 7242, 'row': 7243, \"m's\": 7244, 'kitkat': 7245, '😢': 7246, 'suger': 7247, 'olivia': 7248, 'audition': 7249, 'injury': 7250, 'appendix': 7251, 'appendicitis': 7252, 'fack': 7253, 'nhl': 7254, 'khamis': 7255, 'reaaly': 7256, 'naomi': 7257, 'contemporary': 7258, 'slacke': 7259, '565': 7260, 'jahat': 7261, 'discount': 7262, 'thorpe': 7263, 'nicely': 7264, 'esnho': 7265, 'node': 7266, 'directx': 7267, 'p2': 7268, 'uploaded': 7269, 'blackberry': 7270, 'shitty': 7271, 'povertyyouareevil': 7272, 'struggle': 7273, 'emm': 7274, 'elgin': 7275, 'vava': 7276, 'makati': 7277, '💛': 7278, 'baon': 7279, 'soak': 7280, 'mush': 7281, \"they'd\": 7282, 'ouat': 7283, 'blinkin': 7284, 'headack': 7285, 'tension': 7286, 'eritation': 7287, 'frustrated': 7288, 'perspective': 7289, 'endlessly': 7290, 'blush': 7291, 'kiddo': 7292, 'rumbelle': 7293, 'overwhelming': 7294, 'irresponsibly': 7295, 'pakighinabi': 7296, 'pinkfinite': 7297, 'beb': 7298, 'migraine': 7299, 'coyote': 7300, 'headache': 7301, '인피니트': 7302, 'baechu': 7303, 'calibraskaep': 7304, 'elgato': 7305, 'ant': 7306, 'unexpect': 7307, 'faint': 7308, 'bp': 7309, 'subway': 7310, 'fragile': 7311, 'gap': 7312, 'plot': 7313, 'bungie': 7314, 'woohyun': 7315, 'guilty': 7316, 'davao': 7317, 'luckyyy': 7318, 'confidence': 7319, 'eunhae': 7320, 'misplace': 7321, 'den': 7322, 'dae': 7323, 'bap': 7324, 'huehue': 7325, 'rice': 7326, 'krispy': 7327, 'marshmallow': 7328, 'm5m6junction': 7329, 'soulsurvivor': 7330, 'stafford': 7331, 'progress': 7332, 'mixture': 7333, \"they've\": 7334, 'shems': 7335, 'lage': 7336, 'ramd': 7337, 'opening': 7338, 'munchkin': 7339, 'parting': 7340, 'juja': 7341, 'murugan': 7342, 'bgtau': 7343, 'harap': 7344, 'bagi': 7345, 'aminn': 7346, 'fraand': 7347, '😬': 7348, 'bigbang': 7349, 'sian': 7350, 'nicoleapage': 7351, 'surprised': 7352, 'hellish': 7353, 'thirstyyy': 7354, 'chesties': 7355, \"nando's\": 7356, 'bow': 7357, 'hen': 7358, 'rdd': 7359, 'dissipate': 7360, 'capeee': 7361, 'japan': 7362, 'outlive': 7363, 'x-ray': 7364, 'dental': 7365, 'spine': 7366, 'relief': 7367, 'popol': 7368, 'stomach': 7369, 'frog': 7370, 'brad': 7371, 'gen.ad': 7372, 'negotiable': 7373, 'huhuhuhuhu': 7374, 'bbmadeinmanila': 7375, 'findavip': 7376, 'boyirl': 7377, 'yasss': 7378, '6th': 7379, 'june': 7380, 'laine': 7381, 'difficiency': 7382, 'speed': 7383, 'rapist': 7384, 'commit': 7385, 'crime': 7386, 'bachpan': 7387, 'yaadein': 7388, 'finnair': 7389, 'heathrow': 7390, 'norwegian': 7391, ':\\\\': 7392, 'upvotes': 7393, 'keeno': 7394, 'whatthefuck': 7395, 'grotty': 7396, 'seeker': 7397, 'morality': 7398, 'fern': 7399, 'mimi': 7400, 'bali': 7401, 'editing': 7402, 'lowbat': 7403, 'funk': 7404, 'wewanticecream': 7405, 'sweat': 7406, 'eugh': 7407, 'sara': 7408, 'occasionally': 7409, \"izzy's\": 7410, 'dorm': 7411, 'choppy': 7412, \"infinite's\": 7413, '5:30': 7414, 'cayton': 7415, 'emma': 7416, 'darcey': 7417, 'connor': 7418, 'roommateexperience': 7419, 'avoid': 7420, 'ic': 7421, 'te': 7422, 'auto-followback': 7423, 'ljp': 7424, 'nowdays': 7425, 'attach': 7426, 'numb': 7427, 'dentist': 7428, 'tab': 7429, 'ucas': 7430, 'bigtime': 7431, 'rumor': 7432, 'chin': 7433, 'tickle': 7434, '♫': 7435, 'zikra': 7436, 'lusi': 7437, 'hasya': 7438, 'nugget': 7439, 'olympic': 7440, \"millie's\": 7441, '748292': 7442, 'ano': 7443, '22stans': 7444, 'mag': 7445, 'hateee': 7446, 'lease': 7447, '6g': 7448, 'unsuccessful': 7449, 'earlobes': 7450, 'girls': 7451, 'sue': 7452, 'dreary': 7453, 'denise': 7454, 'murielle': 7455, 'ahouré': 7456, 'pr': 7457, \"kath'd\": 7458, 'respond': 7459, 'chopped': 7460, 'wbu': 7461, 'activity': 7462, 'kme': 7463, 'cram': 7464, 'curious': 7465, 'announcement': 7466, 'trespasser': 7467, 'clandestins': 7468, 'muller': 7469, 'obvious': 7470, 'mufc': 7471, 'stu': 7472, 'buddyyy': 7473, 'feelgoodfriday': 7474, '6:30': 7475, 'babysit': 7476, 'opixer': 7477, '805': 7478, 'pilllow': 7479, 'fool': 7480, 'brag': 7481, 'skrillah': 7482, 'drown': 7483, 'gue': 7484, 'north': 7485, 'sjkaos': 7486, 'disappointed': 7487, 'srry': 7488, 'honma': 7489, 'yeh': 7490, 'walay': 7491, 'bohat': 7492, 'wailay': 7493, 'pre-season': 7494, 'pe': 7495, 'itna': 7496, 'shor': 7497, 'machaya': 7498, 'samjha': 7499, '👍': 7500, '😔': 7501, 'sirkay': 7502, 'wali': 7503, 'pyaaz': 7504, 'daal': 7505, 'onion': 7506, 'vinegar': 7507, 'cooking': 7508, 'tutorial': 7509, 'soho': 7510, 'wobbly': 7511, 'ciao': 7512, 'masaan': 7513, 'muv': 7514, 'beast': 7515, 'hayst': 7516, 'cr': 7517, 'hnnn': 7518, 'optimisation': 7519, 'soniii': 7520, 'kahaaa': 7521, 'freeze': 7522, 'fml': 7523, 'jacket': 7524, 'sleepy': 7525, 'bully': 7526, 'racial': 7527, 'loool': 7528, 'onwards': 7529, 'coincidence': 7530, 'imac': 7531, 'gram': 7532, 'nearer': 7533, 'blaine': 7534, 'darren': 7535, 'fuuuck': 7536, 'gishwhes': 7537, 'exclude': 7538, 'movement': 7539, 'frou': 7540, 'vaccine': 7541, 'armor': 7542, 'legendary': 7543, 'cash': 7544, 'effort': 7545, 'nat': 7546, 'brake': 7547, 'grumpy': 7548, 'wreck': 7549, 'gahhh': 7550, 'terible': 7551, 'kiligs': 7552, 'shravan': 7553, 'maas': 7554, 'stooop': 7555, 'gi-guilty': 7556, 'akooo': 7557, 'imveryverysorry': 7558, 'cd': 7559, 'basename': 7560, 'theme': 7561, 'cigar': 7562, 'speaker': 7563, 'promethazine': 7564, 'zopiclone': 7565, 'addition': 7566, 'quetiapine': 7567, 'modified': 7568, 'prescription': 7569, 'greska': 7570, 'macedonian': 7571, 'slovak': 7572, 'hike': 7573, 'zokay': 7574, 'accent': 7575, 'b-but': 7576, 'gintama': 7577, 'shinsengumi': 7578, 'chapter': 7579, 'crapple': 7580, 'agrees': 7581, 'ftw': 7582, 'phandroid': 7583, 'tline': 7584, 'orchestra': 7585, 'rehearsal': 7586, 'bittersweetness': 7587, 'eunji': 7588, 'bakit': 7589, '121st': 7590, 'ehdar': 7591, 'pegea': 7592, 'panga': 7593, 'dosto': 7594, 'nd': 7595, 'real_liam_payne': 7596, '3/10': 7597, 'dmed': 7598, '23': 7599, 'alreaddyyy': 7600, 'luceleva': 7601, 'naeun': 7602, \"son's\": 7603, 'kidney': 7604, 'ink': 7605, 'bullying': 7606, 'ihatesomepeople': 7607, 'table': 7608, '0-2': 7609, 'hard-wired': 7610, 'canadian': 7611, 'enjoyed': 7612, 'acne': 7613, 'gulo': 7614, 'kandekjs': 7615, 'rize': 7616, 'meydan': 7617, 'fcking': 7618, 'crei': 7619, 'connection': 7620, 'dormmates': 7621, 'bo3': 7622, 'activation': 7623, 'cod': 7624, 'redeem': 7625, 'invalid': 7626, 'hopia': 7627, 'editor': 7628, 'reveal': 7629, 'booo': 7630, 'extension': 7631, 'rightnow': 7632, 'btu': 7633, 'karaoke': 7634, 'licence': 7635, 'apb': 7636, 'hahahaokay': 7637, 'basara': 7638, 'capcom': 7639, 'url': 7640, 'grumble': 7641, 'migrant': 7642, 'awsme': 7643, 'picking': 7644, 'tmw': 7645, 'uwu': 7646, 'jinki': 7647, 'taems': 7648, 'gifs': 7649, 'cambridge': 7650, 'viathe': 7651, 'cyprus': 7652, 'zayncomebackto': 7653, 'spazzing': 7654, 'soobin': 7655, '27': 7656, 'float': 7657, 'pressure': 7658, 'lifetime': 7659, 'hiondsheings': 7660, '58543': 7661, 'sexdate': 7662, \"demi's\": 7663, 'junjou': 7664, 'romantica': 7665, 'privilege': 7666, 'mixtape': 7667, 'convince': 7668, 'friex': 7669, 'shaylan': 7670, '4:20': 7671, 'ylona': 7672, 'nah': 7673, 'waitting': 7674, 'noon': 7675, 'ouh': 7676, 'nm': 7677, 'encanta': 7678, 'vale': 7679, 'osea': 7680, 'bea': 7681, '♛': 7682, '》': 7683, 'beli̇eve': 7684, 'wi̇ll': 7685, 'justi̇n': 7686, '350': 7687, 'ｓｅｅ': 7688, 'ｍｅ': 7689, '349': 7690, 'baek': 7691, 'dunwan': 7692, 'suan': 7693, 'haiz': 7694, '348': 7695, 'adult': 7696, '347': 7697, '😕': 7698, 'insonia': 7699, '346': 7700, 'rick': 7701, 'ross': 7702, 'heartbreaking': 7703, '345': 7704, 'millie': 7705, 'diff': 7706, 'golden': 7707, 'rosebury': 7708, 'familyhome': 7709, '344': 7710, 'monkey': 7711, '343': 7712, 'erica': 7713, 'istg': 7714, 'jackson': 7715, 'nsbzhdnxndamal': 7716, '342': 7717, '11:15': 7718, '2hours': 7719, '11:25': 7720, '341': 7721, 'mahilig': 7722, 'mam-bully': 7723, 'mtaani': 7724, 'tunaita': 7725, 'viazi': 7726, 'choma': 7727, 'jerk': 7728, 'menille': 7729, '340': 7730, \"kam's\": 7731, 'meee': 7732, 'diz': 7733, 'biooo': 7734, 'ay': 7735, 'taray': 7736, 'yumu-youtuber': 7737, '339': 7738, 'parijat': 7739, 'willmissyouparijat': 7740, 'jolly': 7741, '338': 7742, 'mcnuggets': 7743, 'sophie': 7744, 'caramello': 7745, 'koala': 7746, 'suckmejimin': 7747, '337': 7748, 'sucky': 7749, 'dying': 7750, 'pou': 7751, 'goddamn': 7752, 'nje': 7753, 'dbn': 7754, '🎀': 7755, '336': 7756, '335': 7757, 'supporting': 7758, 'pledge': 7759, 'viber': 7760, 'mwah': 7761, 'estate': 7762, 'lansi': 7763, '334': 7764, 'hp': 7765, 'waah': 7766, 'vandag': 7767, 'kgola': 7768, 'neng': 7769, 'eintlik': 7770, 'porn': 7771, '4like': 7772, 'repost': 7773, '333': 7774, 'magpie': 7775, '22.05': 7776, '15-24': 7777, '05.15': 7778, 'chswiyfxcskcalum': 7779, 'nvm': 7780, 'foof': 7781, '332': 7782, 'casillas': 7783, 'manchester': 7784, 'xi': 7785, 'rmtour': 7786, 'eating': 7787, 'irl': 7788, 'blooper': 7789, 'huhuhuhu': 7790, 'na-take': 7791, 'sorta': 7792, 'unfriend': 7793, 'greysonchance': 7794, 'sandwich': 7795, 'belle': 7796, 'sebastian': 7797, 'rewatched': 7798, 's4': 7799, 'sers': 7800, 'heart-breaking': 7801, 'outdated': 7802, 'm4': 7803, 'theater': 7804, '7-3': 7805, '7.30-': 7806, 'ekk': 7807, 'giriboy': 7808, 'danni': 7809, 'harriet': 7810, 'gegu': 7811, 'gray': 7812, '331': 7813, 'politics': 7814, 'blaming': 7815, '68': 7816, 'corbyn': 7817, \"labour's\": 7818, 'ry': 7819, 'lfccw': 7820, '5ever': 7821, 'ontheroadagain': 7822, 'halaaang': 7823, 'recieved': 7824, 'flop': 7825, 'caesarspalace': 7826, 'socialrewards': 7827, 'cali': 7828, 'fuckboys': 7829, '330': 7830, 'chrompet': 7831, 'immune': 7832, 'lush': 7833, 'bathtub': 7834, 'mysql': 7835, 'libmysqlclient-dev': 7836, 'dev': 7837, 'pleasanton': 7838, 'wala': 7839, '329': 7840, 'heed': 7841, '328': 7842, 'gwss': 7843, 'thankyouu': 7844, 'charade': 7845, 'piano': 7846, '327': 7847, 'complaint': 7848, 'yelling': 7849, 'whatsoever': 7850, 'pete': 7851, 'wentz': 7852, 'shogi': 7853, 'blameshoghicp': 7854, 'classmate': 7855, 'fixedgearfrenzy': 7856, 'dispatch': 7857, 'theyre': 7858, \"shamuon's\": 7859, 'toe': 7860, 'horrendously': 7861, \"someone's\": 7862, '326': 7863, 'hasb': 7864, 'atty': 7865, 'mujy': 7866, 'sirf': 7867, 'sensible': 7868, 'brum': 7869, 'cyclerevolution': 7870, 'caaannnttt': 7871, 'overdraw': 7872, 'tbf': 7873, 'perfume': 7874, 'sample': 7875, 'chanel': 7876, 'burberry': 7877, 'prada': 7878, '325': 7879, 'noesss': 7880, 'topgear': 7881, 'bridesmaid': 7882, 'nhs': 7883, \"tomorrow's\": 7884, 'gathering': 7885, 'sudden': 7886, '324': 7887, 'randomrestart': 7888, 'randomreboot': 7889, 'lumia': 7890, 'windowsphone': 7891, \"microsoft's\": 7892, 'addressing': 7893, 'mañana': 7894, 'rappings': 7895, 'striker': 7896, 'lvg': 7897, 'refurbish': 7898, 'cintiq': 7899, 'originate': 7900, \"finnick's\": 7901, 'askfinnick': 7902, 'container': 7903, 'hairy': 7904, '323': 7905, 'bury': 7906, 'omaygad': 7907, 'vic': 7908, 'surgery': 7909, 'tt.tt': 7910, 'hyper': 7911, '322': 7912, 'imiss': 7913, '321': 7914, '320': 7915, 'know.for': 7916, 'prepay': 7917, '319': 7918, 'grandma': 7919, \"grandpa's\": 7920, 'cow': 7921, 'sheeps': 7922, 'vegetable': 7923, 'delirious': 7924, 'motilium': 7925, 'shite': 7926, '318': 7927, 'schoolwork': 7928, \"phoebe's\": 7929, '317': 7930, 'pothole': 7931, '316': 7932, '1,300': 7933, 'robyn': 7934, 'necklace': 7935, 'rachel': 7936, 'ramzan': 7937, 'clapham': 7938, 'investigate': 7939, 'sth': 7940, 'essentially': 7941, 'photoshooot': 7942, 'mahone': 7943, 'shut': 7944, 'andaming': 7945, 'memorization': 7946, 'cotton': 7947, 'swallow': 7948, 'snot': 7949, 'taknottem': 7950, '477': 7951, 'btob': 7952, 'percentage': 7953, 'swift': 7954, 'a9': 7955, 'sexyjane': 7956, 'horny': 7957, 'goodmusic': 7958, 'lart': 7959, 'sew': 7960, 'orange': 7961, 'skyfall': 7962, 'premiere': 7963, 'manteca': 7964, \"she'd\": 7965, 'shiatsu': 7966, 'setting': 7967, 'risk': 7968, 'hopper': 7969, 'eyyah': 7970, 'utd': 7971, 'born': 7972, '1-0': 7973, 'cart': 7974, 'aaa': 7975, 'waifu': 7976, 'breakup': 7977, 'bias': 7978, 'syndrome': 7979, 'shy': 7980, 'pixelated': 7981, 'weh': 7982, 'maymay': 7983, 'advance': 7984, 'allowance': 7985, 'magpaalam': 7986, 'tf': 7987, 'subtitle': 7988, 'chang': 7989, 'backstory': 7990, 'gimme': 7991, 'meal': 7992, 'neat-o': 7993, 'wru': 7994, 'scissors': 7995, 'creation': 7996, 'amtired': 7997, 'imysm': 7998, 'tut': 7999, 'trop': 8000, 'tard': 8001, 'deadline': 8002, 'st': 8003, 'premiun': 8004, 'making': 8005, 'notcool': 8006, '2/3': 8007, 'lahat': 8008, 'araw': 8009, 'nag': 8010, 'gyu': 8011, 'lmfaooo': 8012, 'mashup': 8013, 'eu': 8014, 'lcs': 8015, 'yass': 8016, 'relative': 8017, 'yr': 8018, 'sydney': 8019, 'perf': 8020, 'hashtags': 8021, 'omfg': 8022, 'combat': 8023, 'dosent': 8024, \"sod's\": 8025, '20mins': 8026, 'yahoo': 8027, 'yodel': 8028, 'jokingly': 8029, 'seriousness': 8030, 'gahd': 8031, 'zayns': 8032, '26th': 8033, '12.00': 8034, 'obyun': 8035, 'wayhh': 8036, 'poisoning': 8037, 'prevalent': 8038, 'controversy': 8039, '🍵': 8040, 'tube': 8041, 'strike': 8042, 'meck': 8043, 'mcfc': 8044, 'ucan': 8045, 'depressing': 8046, 'poc': 8047, 'sms': 8048, 'specific': 8049, 'sinhala': 8050, 'billionaire': 8051, '1645': 8052, '1190': 8053, 'maldives': 8054, 'dheena': 8055, 'fasgadah': 8056, 'alvadhaau': 8057, 'countdown': 8058, 'function': 8059, 'desktop': 8060, 'evelineconrade': 8061, 'kikmsn': 8062, 'selfshot': 8063, 'backkk': 8064, 'transfer': 8065, 'relaxing': 8066, 'dull': 8067, 'overcast': 8068, 'missin': 8069, 'hangin': 8070, 'wiff': 8071, 'interactive': 8072, 'cherry': 8073, 'bakewell': 8074, 'collect': 8075, 'teal': 8076, 'sect': 8077, 'tennunb': 8078, 'skip': 8079, 'doomsday': 8080, 'neglected': 8081, 'postie': 8082, 'bellamy': 8083, 'raven': 8084, 'clarke': 8085, 'helmy': 8086, 'uh': 8087, 'cnt': 8088, 'whereisthesun': 8089, 'summerismissing': 8090, 'longgg': 8091, 'ridiculous': 8092, 'stocko': 8093, 'lucozade': 8094, 'shooting': 8095, 'explosion': 8096, 'beh': 8097, 'half-remembered': 8098, \"melody's\": 8099, 'recall': 8100, 'difficult': 8101, 'expo': 8102, 'jisoo': 8103, 'anon': 8104, 'mager': 8105, 'wi': 8106, 'wht': 8107, 'distant': 8108, 'buffering': 8109, 'insane': 8110, 'charli': 8111, 'ganas': 8112, 'studio': 8113, 'arch': 8114, 'lyin': 8115, 'kian': 8116, 'supercars': 8117, 'gurgaon': 8118, 'location': 8119, '9:15': 8120, 'satire': 8121, 'peanut': 8122, 'viners': 8123, 'palembang': 8124, 'sorrryyy': 8125, 'fany': 8126, 'boner': 8127, 'mercy': 8128, 'yuki': 8129, '2500k': 8130, 'jake': 8131, 'gyllenhaal': 8132, 'impact': 8133, \"ledger's\": 8134, 'b4': 8135, 'deplete': 8136, 'mbasa': 8137, 'aah': 8138, 'pa-copy': 8139, 'biome': 8140, 'mosque': 8141, 'smelly': 8142, 'annoyed': 8143, \"ciara's\": 8144, \"everything's\": 8145, 'hugs': 8146, 'tall': 8147, 'intention': 8148, 'ambs': 8149, \"harry's\": 8150, 'mayday': 8151, 'parade': 8152, 'lyf': 8153, '13th': 8154, 'animal': 8155, 'chris': 8156, 'brown': 8157, 'risky': 8158, 'cologne': 8159, 'duo': 8160, 'ballad': 8161, 'bish': 8162, 'intern': 8163, 'yumyum': 8164, \"cathy's\": 8165, 'missyou': 8166, 'bishes': 8167, 'ruby': 8168, 'pora': 8169, 'karlia': 8170, 'khatam': 8171, 'bandi': 8172, '👑': 8173, 'pyaari': 8174, 'gawd': 8175, 'massis': 8176, 'thatselfiethough': 8177, 'loop': 8178, 'aishhh': 8179, 'viewer': 8180, 'toffee': 8181, 'honesty': 8182, 'cheatday': 8183, 'protein': 8184, 'sissi': 8185, 'tote': 8186, 'slowly': 8187, 'breaking': 8188, 'church': 8189, 'pll': 8190, 'sel': 8191, 'serbia': 8192, 'serbian': 8193, 'selenators': 8194, 'motavators': 8195, 'zayyyn': 8196, 'happend': 8197, 'imperative': 8198, 'panas': 8199, 'sake': 8200, 'hamstring': 8201, 'rodwell': 8202, 'trace': 8203, 'tp': 8204, 'powder': 8205, 'wider': 8206, 'waking': 8207, 'bruno': 8208, '1.8': 8209, 'ed': 8210, 'croke': 8211, 'toll': 8212, 'shape': 8213, 'unluckiest': 8214, 'bettor': 8215, 'nstp': 8216, 'sem': 8217, 'tan': 8218, 'chipotle': 8219, 'chick-fil-a': 8220, 'stole': 8221, 'ramadhan': 8222, 'stexpert': 8223, 'ripstegi': 8224, 'nickyyy': 8225, '¿': 8226, 'emotion': 8227, 'centralise': 8228, 'discontinue': 8229, 'disappointment': 8230, 'sniff': 8231, \"i'ts\": 8232, 'therese': 8233, 'cred': 8234, 't_t': 8235, 'eliminate': 8236, 'teamzipal': 8237, 'smtm': 8238, 'assingnment': 8239, 'editied': 8240, 'nakaka': 8241, 'beastmode': 8242, 'gaaawd': 8243, 'colombia': 8244, 'yots': 8245, 'labyo': 8246, 'pano': 8247, 'nalamannn': 8248, 'hardheaded': 8249, \"zach's\": 8250, 'xpress': 8251, 'hopkins': 8252, 'melatonin': 8253, '2-4': 8254, 'hahaah': 8255, 'frequently': 8256, 'jail': 8257, 'weirddd': 8258, 'donghyuk': 8259, 'stans': 8260, 'beks': 8261, 'reynoldsgrl': 8262, 'ole': 8263, 'beardy': 8264, 'kaussies': 8265, 'pixels': 8266, 'bummer': 8267, 'fightingmcirene': 8268, \"michael's\": 8269, 'exercising': 8270, 'miserable': 8271, '💦': 8272, '💃🏽': 8273, 'shouldve': 8274, 'saffron': 8275, 'peasant': 8276, 'wouldve': 8277, 'nfinite': 8278, 'admin_myung': 8279, 'slp': 8280, 'laomma': 8281, 'kebaya': 8282, 'bandung': 8283, '7df89150': 8284, '62': 8285, '08962464174': 8286, 'laomma_couture': 8287, 'haizzz': 8288, 'urghhh': 8289, 'sat': 8290, 'working-on-a-tight-schedule': 8291, 'ganbarimasu': 8292, 'livid': 8293, 'whammy': 8294, 'quuuee': 8295, 'friooo': 8296, 'raining': 8297, 'stereo': 8298, 'chwang': 8299, 'lorm': 8300, '823': 8301, 'unhappy': 8302, 'lolzz': 8303, 'dats': 8304, 'corey': 8305, 'mahirap': 8306, 'noodle': 8307, 'veeerry': 8308, 'orig': 8309, 'starholicxx': 8310, '07:17': 8311, '@the': 8312, 'notr': 8313, 'hwy': 8314, 'niall': 8315, 'fraud': 8316, 'diplomacy': 8317, 'survival': 8318, 'zero': 8319, 'tolerant': 8320, 'pier': 8321, 'approach': 8322, 'rattle': 8323, 'robe': 8324, 'emphasis': 8325, 'abby.can': 8326, 'persuade': 8327, 'lyric': 8328, \"emily's\": 8329, 'elect': 8330, 'kamiss': 8331, 'mwa': 8332, 'cafe': 8333, 'melbourne': 8334, 'anyonneee': 8335, 'fricken': 8336, 'rito': 8337, 'friendzone': 8338, 'panel': 8339, 'hsm': 8340, 'canarios': 8341, 'ukiss': 8342, 'kurt': 8343, \"fatma'm\": 8344, 'lmfao': 8345, 'flapjack': 8346, 'countthecost': 8347, 'ihop': 8348, 'infra': 8349, 'lq': 8350, 'sotired': 8351, 'mybrainneedstoshutoff': 8352, 'maccies': 8353, '510': 8354, 'silicon': 8355, 'kbye': 8356, 'ini': 8357, 'citizen': 8358, 'ranking': 8359, 'mcountdown': 8360, '5h': 8361, 'thapelo': 8362, 'civ': 8363, 'wooden': 8364, 'mic': 8365, 'embarrassing': 8366, 'organization': 8367, 'translate': 8368, 'mecha-totems': 8369, 'nak': 8370, 'tgk': 8371, 'jokid': 8372, 'rent': 8373, 'inconsiderate': 8374, 'softball': 8375, 'tomcat': 8376, 'chel': 8377, 'jemma': 8378, 'matchy': 8379, 'elsa': 8380, 'postpone': 8381, 'karin': 8382, 'vist': 8383, 'unhealthy': 8384, 'propa': 8385, 'knockin': 8386, 'pre-holiday': 8387, 'meany': 8388, 'deathbybaconsmell': 8389, 'inital': 8390, 'destination': 8391, 'victoria': 8392, 'luna': 8393, 'krystal': 8394, 'sarajevo': 8395, 'haix': 8396, 'sp': 8397, 'wii': 8398, 'bayonetta': 8399, 'doable': 8400, 'drove': 8401, 'moved': 8402, 'agency': 8403, 'story.miss': 8404, 'everone': 8405, 'jps': 8406, 'mamabear': 8407, 'imintoher': 8408, 'underrated': 8409, \"slovakia's\": 8410, 'D:': 8411, 'saklap': 8412, 'rizal': 8413, 'lib': 8414, 'advisory': 8415, 'period': 8416, 'dit': 8417, 'dus': 8418, 'harsh': 8419, 'ohgod': 8420, 'abligaverins': 8421, 'sexygirlbypreciouslemmy': 8422, 'ripsandrabland': 8423, 'cri': 8424, 'edel': 8425, 'salam': 8426, 'mubark': 8427, 'dong': 8428, 'tammirossm': 8429, 'speck': 8430, 'abbymill': 8431, 'ion': 8432, '5min': 8433, 'hse': 8434, 'noob': 8435, 'fck': 8436, 'nae': 8437, 'whit': 8438, 'van': 8439, 'bristol': 8440, 'subserver': 8441, 'oo': 8442, 'tub': 8443, 'penyfan': 8444, 'breconbeacons': 8445, 'tittheir': 8446, '42': 8447, 'hottie': 8448, 'fuzzy': 8449, 'antonio': 8450, 'kang': 8451, 'junhee': 8452, 'couldve': 8453, 'pz': 8454, 'somerset': 8455, 'sunburnt': 8456, 'safer': 8457, 'k3g': 8458, 'input': 8459, 'gamestomp': 8460, 'desc': 8461, \"angelo's\": 8462, 'yna': 8463, 'fiver': 8464, 'sakho': 8465, 'threat': 8466, 'goalscorer': 8467, '10:59': 8468, '11.00': 8469, 'sham': 8470, 'tricky': 8471, 'baao': 8472, 'nisrina': 8473, 'bcs': 8474, 'ladygaga': 8475, \"you's\": 8476, 'marrish': 8477, \"otp's\": 8478, 'edomnt': 8479, 'qih': 8480, 'shxbs': 8481, 'chilton': 8482, 'creepy': 8483, 'boohoo': 8484, 'roar': 8485, 'victory': 8486, 'tweepsmatchout': 8487, 'nein': 8488, '404': 8489, 'willlow': 8490, 'sowwy': 8491, '3000': 8492, 'gear': 8493, '0.001': 8494, 'mode': 8495, 'madi': 8496, '11:11': 8497, 'shanzay': 8498, 'salabraty': 8499, 'journo': 8500, 'lure': 8501, 'mashaket': 8502, 'bapak': 8503, 'prima': 8504, 'mune': 8505, '874': 8506, 'plisss': 8507, 'sunway': 8508, 'petaling': 8509, 'jaya': 8510, 'selangor': 8511, 'huhuu': 8512, 'margo': 8513, 'konga': 8514, 'wa': 8515, 'ode': 8516, 'disvirgined': 8517, 'negotiate': 8518, 'bride': 8519, 'yulin': 8520, 'imma': 8521, 'syawal': 8522, 'lapar': 8523, 'foundation': 8524, 'facil': 8525, 'dh': 8526, 'chalet': 8527, 'suay': 8528, 'anot': 8529, 'bugger': 8530, 'एक': 8531, 'बार': 8532, 'फिर': 8533, 'सेँ': 8534, 'धोखा': 8535, 'chandauli': 8536, 'majhwar': 8537, 'tito': 8538, 'titas': 8539, 'critical': 8540, 'narcos': 8541, 'regens': 8542, 'unfaved': 8543, 'benadryl': 8544, 'arent': 8545, 'yg': 8546, 'gg': 8547, 'sxrew': 8548, 'dissappeared': 8549, 'swap': 8550, 'ishal': 8551, 'thaanks': 8552, 'jhezz': 8553, 'defence': 8554, 'defensive': 8555, 'nrltigersroosters': 8556, 'indiana': 8557, 'hibbs': 8558, 'biblethump': 8559, 'rlyyy': 8560, 'septum': 8561, 'pierce': 8562, 'venomous': 8563, 'carriage': 8564, 'fur-trimmed': 8565, 'stetson': 8566, 'error': 8567, '59': 8568, 'xue': 8569, 'midori': 8570, 'disabled': 8571, 'sakit': 8572, 'mateo': 8573, 'bartender': 8574, 'despair': 8575, 'insta': 8576, 'iwantin': 8577, '___': 8578, 'fault': 8579, 'help@veryhq.co.uk': 8580, 'benedictervention': 8581, '221b': 8582, 'popcorn': 8583, 'joyce': 8584, 'ooops': 8585, 'paalam': 8586, 'sazballs': 8587, 'incident': 8588, 'aaahh': 8589, \"stomach's\": 8590, 'growl': 8591, 'beard': 8592, 'nooope': 8593, 'hundred': 8594, 'meg': 8595, \"verity's\": 8596, 'rupert': 8597, 'pleaaase': 8598, '👆🏻': 8599, 'woaah': 8600, 'solvo': 8601, 'twin': 8602, 'lego': 8603, 'barefooted': 8604, 'twelvyy': 8605, 'boaz': 8606, 'myhill': 8607, 'takeover': 8608, 'wba': 8609, \"taeyeon's\": 8610, 'derp': 8611, 'pd': 8612, 'zoom': 8613, \"sunny's\": 8614, 'besst': 8615, 'plague': 8616, 'pit': 8617, 'frail': 8618, 'twurkin': 8619, 'razzist': 8620, 'tumblr': 8621, 'shek': 8622, '609': 8623, 'mugshot': 8624, 'plsss': 8625, 'taissa': 8626, 'farmiga': 8627, 'ahs': 8628, 'danielle': 8629, 'software': 8630, 'restore': 8631, 'momo': 8632, 'pharma': 8633, 'immovable': 8634, 'messy': 8635, 'anshe': 8636, 'f1': 8637, 'rand': 8638, 'bein': 8639, 'tla': 8640, 'tweng': 8641, 'gene': 8642, 'up.come': 8643, 'county': 8644, 'minhyuks': 8645, '1900': 8646, '😪': 8647, 'hz': 8648, 'emta': 8649, 'hatigii': 8650, 'b2aa': 8651, 'anesthesia': 8652, 'penrith': 8653, 'plain': 8654, 'untouched': 8655, 'brienne': 8656, 'lsh': 8657, 'gunna': 8658, 'former': 8659, 'darn': 8660, 'juudiciary': 8661, \"horton's\": 8662, 'dunkin': 8663, 'socialise': 8664, 'cara': 8665, \"delevingne's\": 8666, 'lace': 8667, 'fank': 8668, 'takfaham': 8669, 'older': 8670, 'ufff': 8671, 'sr': 8672, 'dard': 8673, 'katekyn': 8674, 'ehh': 8675, 'hacharatt': 8676, 'niwll': 8677, 'depend': 8678, 'successful': 8679, 'goa': 8680, 'linis': 8681, 'kasi': 8682, 'sweating': 8683, 'init': 8684, 'rhd': 8685, 'celebration': 8686, 'physical': 8687, 'wae': 8688, 'subsidized': 8689, '20th': 8690, 'youngjae': 8691, 'harumph': 8692, 'soggy': 8693, 'weeding': 8694, 'sakura': 8695, 'flavour': 8696, 'chokkie': 8697, '🌸': 8698, 'unavailable': 8699, 'richard': 8700, 'satya': 8701, 'aditya': 8702, '🍜': 8703, 'vibrate': 8704, 'cu': 8705, 'dhaka': 8706, 'cornettos': 8707, 'nosebleed': 8708, 'nintendo': 8709, 'wew': 8710, 'ramos': 8711, 'ground': 8712, 'shawn': 8713, 'mend': 8714, 'dinghy': 8715, 'skye': 8716, 'colleague': 8717, 'gagal': 8718, 'txt': 8719, 'sims': 8720, 'nooot': 8721, 'notch': 8722, 'thts': 8723, 'everyones': 8724, 'starve': 8725, '\\U000fe196': 8726, 'pyjama': 8727, 'suks': 8728, 'sleeping': 8729, 'swifties': 8730, 'sorna': 8731, 'lurgy': 8732, '6gb': 8733, 'fenestoscope': 8734, 'etienne': 8735, 'bandana': 8736, 'vagina': 8737, 'suriya': 8738, 'dangle': 8739, 'mjhe': 8740, 'aaj': 8741, 'kisi': 8742, 'kiya': 8743, 'eyesight': 8744, '25x30': 8745, 'aftenoon': 8746, 'booore': 8747, 'boyfriend': 8748, 'garage': 8749, 'gws': 8750, 'anatomy': 8751, 'no1': 8752, \"morisette's\": 8753, 'non-trial': 8754, 'sayhername': 8755, 'lootcrate': 8756, 'inca': 8757, 'trail': 8758, 'sandboarding': 8759, 'derby': 8760, 'unable': 8761, 'signature': 8762, 'dish': 8763, 'unfamiliar': 8764, 'shed': 8765, \"old's\": 8766, '14518344': 8767, '61': 8768, 'thirdwheeling': 8769, 'lovebird': 8770, 'imo': 8771, '@juliettemaughan': 8772, 'sensiesha': 8773, 'eldest': 8774, '😟': 8775, 'keedz': 8776, 'taybigail': 8777, 'tournament': 8778, 'ps4': 8779, 'kink': 8780, 'losing': 8781, 'streak': 8782, 'srsky': 8783, 'tdc': 8784, 'in-sensitiveness': 8785, 'cooperate': 8786, 'conversion': 8787, 'thurston': 8788, 'collins': 8789, 'quietly': 8790, 'kennel': 8791, '911': 8792, 'pluckersss': 8793, 'gion': 8794, '886': 8795, 'kidschoiceawards': 8796, 'ming': 8797, 'pbr': 8798, 'shoutout': 8799, 'periscope': 8800, 'uts': 8801, 'shawty': 8802, 'naw': 8803, \"sterling's\": 8804, '9muses': 8805, 'hrryok': 8806, 'wnt': 8807, '9:30': 8808, '9:48': 8809, '9/11': 8810, 'bueno': 8811, 'receptionist': 8812, 'ella': 8813, 'ketchup': 8814, 'tasteless': 8815, 'deantd': 8816, 'justgotkanekified': 8817, 'babes': 8818, 'notgonnabeactivefor': 8819, '2weeksdontmissittoomuch': 8820, '2013': 8821, 'vlog': 8822, 'turtle': 8823, 'cnn': 8824, 'strapline': 8825, 'theatre': 8826, 'guncontrol': 8827, \"thát's\": 8828, 'powerpoint': 8829, 'expectation': 8830, 'diner': 8831, 'no-no': 8832, 'hinde': 8833, 'circuit': 8834, 'secondary': 8835, 'sodders': 8836, 'mobitel': 8837, 'playstation': 8838, 'exp': 8839, 'misspell': 8840, 'hyungwon': 8841, 'needicecreamnow': 8842, 'repeatedly': 8843, 'nu-uh': 8844, 'jace': 8845, 'most': 8846, 'urgh': 8847, \"grigson's\": 8848, 'carrot': 8849, '>:-(': 8850, 'ughh': 8851, 'otter': 8852, 'protection': 8853, 'argh': 8854, 'pon': 8855, 'otl': 8856, 'sleepover': 8857, 'jesse': 8858, 'fabina': 8859, 'meant': 8860, 'gardening': 8861, \"barrista's\": 8862, 'pup': 8863, 'brolly': 8864, 'dey': 8865, 'bitin': 8866, 'pretzel': 8867, 'bb17': 8868, 'bblf': 8869, 'fuckin': 8870, 'vanilla': 8871, 'latte': 8872, 'skulker': 8873, 'thread': 8874, 'hungrrryyy': 8875, 'icloud': 8876, 'ipod': 8877, 'hallyu': 8878, 'über': 8879, 'okie': 8880, '8p': 8881, 'harlo': 8882, 'torrentialrain': 8883, 'lloyd': 8884, 'knowww': 8885, 'runny': 8886, 'sweater': 8887, 'intolerant': 8888, 'xenophobes': 8889, 'wtfff': 8890, 'tone': 8891, '1pm': 8892, 'pish': 8893, 'comparison': 8894, 'remastered': 8895, 'fe14': 8896, 'cornetto': 8897, 'strawberry': 8898, 'kapatidkongpogi': 8899, 'mel': 8900, 'carmen': 8901, 'login': 8902, '00128835': 8903, 'wingstop': 8904, 'budge': 8905, 'fuq': 8906, 'ilhoon': 8907, 'getthescoop': 8908, 'hearess': 8909, '677': 8910, 'txt_shot': 8911, 'unfollowing': 8912, 'standby': 8913, 'inatall': 8914, 'zenmate': 8915, 'namechecking': 8916, 'whistle': 8917, 'junmyeon': 8918, 'ddy': 8919, 'arini': 8920, 'je': 8921, 'igbo': 8922, 'blamehoney': 8923, 'whhr': 8924, 'snuggle': 8925, 'usage': 8926, 'warning': 8927, 'tweeting': 8928, 'animator': 8929, 'vertigo': 8930, 'panic': 8931, 'dual': 8932, 'carriageway': 8933, 'aragalang': 8934, '08': 8935, 'tams': 8936, 'theo': 8937, 'anymoreee': 8938, 'cactus': 8939, 'sorrry': 8940, 'bowel': 8941, 'tumour': 8942, 'puffy': 8943, 'eyelid': 8944, 'musicas': 8945, 'campsite': 8946, 'miah': 8947, 'hahays': 8948, 'churro': 8949, 'montana': 8950, 'reign': 8951, 'example': 8952, 'inflation': 8953, 'sic': 8954, 'reset': 8955, 'entlerbountly': 8956, 'dirtykik': 8957, 'sexcam': 8958, 'spray': 8959, 'postcode': 8960, 'kafi': 8961, 'mene': 8962, 'koi': 8963, 'rewert': 8964, 'bunta': 8965, 'warnaaa': 8966, 'torture': 8967, 'iran': 8968, 'irandeal': 8969, 'us-iran': 8970, 'nuclear': 8971, \"mit's\": 8972, 'severely': 8973, 'li': 8974, 's2e12': 8975, 'rumpy': 8976, 'gallon': 8977, 'responsibility': 8978, 'dandia': 8979, 'rbi': 8980, 'cage': 8981, 'parrot': 8982, '1ly': 8983, 'commission': 8984, 'cag': 8985, 'ily.melanie': 8986, 'unlike': 8987, 'talent': 8988, 'deepxcape': 8989, 'doin': 8990, '5:08': 8991, 'thesis': 8992, 'gtg': 8993, 'compete': 8994, 'vv': 8995, 'respect': 8996, 'nys': 8997, 'opt-outed': 8998, 'vam': 8999, 'testing': 9000, 'speced': 9001, 'ell': 9002, 'sexyamelie': 9003, 'fineandyu': 9004, 'imsorry': 9005, 'koe': 9006, 'emyu': 9007, 'confetti': 9008, 'sini': 9009, 'dipoppo': 9010, 'bestweekend': 9011, 'okay-ish': 9012, 'html': 9013, 'geneva': 9014, 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'rider': 9078, 'hueee': 9079, 'thingy': 9080, 'george': 9081, 'chew': 9082, 'stella': 9083, 'theaccidentalcouple': 9084, 'smooth': 9085, 'handover': 9086, 'spick': 9087, 'offense': 9088, 'bebii': 9089, 'happenend': 9090, 'dr': 9091, 'balm': 9092, 'hmph': 9093, 'bubba': 9094, 'floor': 9095, 'oi': 9096, 'bengali': 9097, 'insecure': 9098, 'masterchef': 9099, 'whatchya': 9100, 'petrol': 9101, 'diesel': 9102, 'cock': 9103, 'nyquil': 9104, 'poootek': 9105, '1,500': 9106, 'bobble': 9107, 'leak': 9108, 'thermos': 9109, 'tae': 9110, 'confusing': 9111, 'kita': 9112, 'ia': 9113, 'developed': 9114, 'corrupted': 9115, 'anything.surely': 9116, 'october': 9117, 'ene': 9118, '3k': 9119, 'zehr': 9120, 'khany': 9121, 'grocery': 9122, 'hubba': 9123, 'gum': 9124, 'closet': 9125, 'jhalak': 9126, 'bakwas': 9127, '. ...': 9128, 'seehiah': 9129, 'goy': 9130, 'nachos': 9131, 'braid': 9132, 'initial': 9133, 'ruth': 9134, 'boong': 9135, 'gta': 9136, 'cwnt': 9137, 'trivia': 9138, 'bdays': 9139, 'rohingya': 9140, 'muslims': 9141, 'indict': 9142, 'trafficking': 9143, 'thailand': 9144, 'rumble': 9145, 'kumble': 9146, 'scold': 9147, 'phrase': 9148, 'tfw': 9149, 'jest': 9150, 'relaxes': 9151, 'offend': 9152, 'sleepingwithsirens': 9153, '17th': 9154, 'bringmethehorizon': 9155, 'carva': 9156, 'regularly': 9157, 'sympathis': 9158, 'revamps': 9159, 'mosquito': 9160, 'headphone': 9161, 'breathing': 9162, 'wacha': 9163, 'niende': 9164, '2hrs': 9165, '13m': 9166, 'kk': 9167, 'calibraksaep': 9168, 'darlin': 9169, 'stunning': 9170, \"doedn't\": 9171, 'meaningful': 9172, 'horrific': 9173, 'scoups': 9174, 'royally': 9175, 'sweedy': 9176, 'nams': 9177, \"sacconejoly's\": 9178, 'bethesda': 9179, 'fallout': 9180, 'likee': 9181, 'minecon': 9182, 'kateee': 9183, 'iloveyouu': 9184, 'linux': 9185, 'nawwwe': 9186, 'chikka': 9187, 'ug': 9188, 'rata': 9189, 'soonest': 9190, 'mwamwa': 9191, 'faggot': 9192, 'opener': 9193, 'fyi': 9194, 'mehendi': 9195, 'dash': 9196, 'bookmark': 9197, 'whay': 9198, 'shaa': 9199, 'pramis': 9200, '😚': 9201, 'ngee': 9202, 'ann': 9203, 'crikey': 9204, 'snit': 9205, 'tiring': 9206, 'nathanielhinanakit': 9207, 'naya': 9208, 'spinny': 9209, 'loading': 9210, 'wheel': 9211, 'notifs': 9212, 'albeit': 9213, 'disappointing': 9214, 'athlete': 9215, 'racing': 9216, 'stripe': 9217, 'gfriend': 9218, 'screenshots': 9219, 'fugly': 9220, 'jongdae': 9221, 'tlists': 9222, 'recommended': 9223, 'budget': 9224, 'pabebegirls': 9225, 'pabebe': 9226, 'sandra': 9227, 'bland': 9228, 'storify': 9229, 'mtvhottest': 9230, 'gaga': 9231, '😵': 9232, 'hulkamania': 9233, 'unloved': 9234, 'ihhh': 9235, 'stackare': 9236, 'remedy': 9237, 'ov': 9238, 'raiz': 9239, 'nvr': 9240, 'gv': 9241, 'up.wt': 9242, 'wt': 9243, 'thr': 9244, 'soln': 9245, \"sister's\": 9246, 'pipe': 9247, 'lawn': 9248, \"cupid's\": 9249, 'retainer': 9250, 'clown': 9251, 'lipstick': 9252, 'haiss': 9253, 'todayy': 9254, 'thoo': 9255, 'everday': 9256, 'hangout': 9257, 'steven': 9258, 'william': 9259, 'umboh': 9260, 'jadines': 9261, 'thiz': 9262, 'iz': 9263, 'emeged': 9264, 'kennat': 9265, 'abi': 9266, 'arctic': 9267, 'chicsirific': 9268, 'structured': 9269, 'cumbia': 9270, 'badlife': 9271, '4-5': 9272, 'kaslkdja': 9273, '3wks': 9274, 'feverfew': 9275, 'weddingflowers': 9276, 'diyflowers': 9277, 'fitnes': 9278, 'wolverine': 9279, 'innocent': 9280, '🙏🏻': 9281, '🎂': 9282, 'mememe': 9283, 'krystoria': 9284, 'snob': 9285, 'zumba': 9286, 'greekcrisis': 9287, 'remain': 9288, 'artistic': 9289, 'dutch': 9290, 'legible': 9291, 'israeli': 9292, 'passport': 9293, 'froze': 9294, '23rd': 9295, 'stomachache': 9296, 'ཀ': 9297, 'agains': 9298, 'otani': 9299, '3-0': 9300, 'niaaa': 9301, '2/4': 9302, 'scheme': 9303, 'fckin': 9304, 'vin': 9305, 'plss': 9306, 'rply': 9307, 'rat': 9308, 'mac': 9309, 'backup': 9310, 'actual': 9311, 'lunes': 9312, 'martes': 9313, 'robinhood': 9314, 'robinhoodies': 9315, '🚙': 9316, 'docopenhagen': 9317, 'setter': 9318, 'swipe': 9319, 'bbygurl': 9320, 'caribbean': 9321, '6yrs': 9322, 'takraw': 9323, 'fersuree': 9324, 'angie': 9325, 'sheriff': 9326, 'aaages': 9327, \"i'mo\": 9328, 'sulk': 9329, 'selfish': 9330, 'nonce': 9331, 'bison': 9332, 'motivate': 9333, \"q'don\": 9334, 'cheat': 9335, 'stomping': 9336, 'aaaaaaaaah': 9337, 'kanye': 9338, 'jdjdjdjd': 9339, \"jimin's\": 9340, 'fancafe': 9341, 'flipping': 9342, 'waffle': 9343, '87.7': 9344, '2fm': 9345, 'himseek': 9346, 'kissme': 9347, 'glo': 9348, 'cory': 9349, 'monteith': 9350, 'hashbrowns': 9351, 'pgs': 9352, 'msc': 9353, 'hierro': 9354, 'shirleycam': 9355, 'looks': 9356, 'gilet': 9357, 'cheek': 9358, 'squishy': 9359, 'donating': 9360, 'lahhh': 9361, 'eon': 9362, 'sunrise': 9363, 'beety': 9364, '697': 9365, 'getaway': 9366, 'criminal': 9367, 'amiibo': 9368, 'habe': 9369, 'siannn': 9370, 'chuckin': 9371, 'ampsha': 9372, 'nia': 9373, 'strap': 9374, 'dz9055': 9375, 'entlead': 9376, '590': 9377, 'nudes': 9378, '07:02': 9379, 'ifsc': 9380, 'mayor': 9381, 'biodiversity': 9382, 'taxonomic': 9383, 'collaboration': 9384, 'specie': 9385, 'collar': 9386, '3:03': 9387, 'belt': 9388, 'smith': 9389, 'eyeliner': 9390, 'therefore': 9391, 'netherlands': 9392, 'el': 9393, 'jeb': 9394, 'blacklivesmatter': 9395, 'slogan': 9396, 'msnbc': 9397, 'jebbush': 9398, 'famish': 9399, 'marino': 9400, 'qualify': 9401, 'suzy': 9402, 'skirt': 9403, 'tama': 9404, 'warrior': 9405, 'wound': 9406, 'iraq': 9407, 'camara': 9408, 'coverall': 9409, 'sneezy': 9410, 'rogerwatch': 9411, 'stalker': 9412, 'velvet': 9413, 'tradition': 9414, 'beheaviour': 9415, \"robert's\": 9416, '.\\n.': 9417, 'aaron': 9418, 'jelouse': 9419, 'mtg': 9420, 'thoughtseized': 9421, 'playables': 9422, 'oldie': 9423, 'goody': 9424, 'mcg': 9425, 'inspirit': 9426, 'ised': 9427, 'assume': 9428, 'waisted': 9429, 'guinness': 9430, 'venue': 9431, 'pepper': 9432, 'thessidew': 9433, '877': 9434, 'genesis': 9435, 'november': 9436, 'mash': 9437, 'whattsap': 9438, 'inuyasha': 9439, 'outfwith': 9440, 'myungsoo': 9441, 'yeol': 9442, 'satisfied': 9443, 'challo': 9444, 'pliss': 9445, 'juliana': 9446, 'enroll': 9447, 'darlene': 9448, 'emoji': 9449, 'brisbane': 9450, 'merlin': 9451, 'nawwwee': 9452, 'hyperbullies': 9453, 'tong': 9454, 'nga': 9455, 'seatmates': 9456, 'rajud': 9457, 'ore': 9458, 'kaylas': 9459, 'ericavan': 9460, 'jong': 9461, 'dongwoo': 9462, 'photocards': 9463, 'wh': 9464, 'dw': 9465, 'tumor': 9466, 'vivian': 9467, 'mmsmalubhangsakit': 9468, 'jillcruz': 9469, 'qt': 9470, '19th': 9471, 'co-worker': 9472, 'starving': 9473, 'unsettled': 9474, 'gh': 9475, '18c': 9476, 'rlly': 9477, 'hamster': 9478, 'sheeran': 9479, 'preform': 9480, 'monash': 9481, 'hitmarker': 9482, 'glitch': 9483, 'safaa': 9484, \"selena's\": 9485, 'galat': 9486, 'tum': 9487, 'ab': 9488, 'lrka': 9489, 'bna': 9490, 'bhook': 9491, 'afterschool': 9492, 'bilal': 9493, 'ashraf': 9494, 'icu': 9495, 'annnd': 9496, 'winchester': 9497, '{:': 9498, 'dms': 9499, 'grepe': 9500, 'grepein': 9501, 'panem': 9502, 'sulli': 9503, 'injured': 9504, 'cpm': 9505, 'condemn': 9506, 'political': 9507, '✔': 9508, 'occur': 9509, 'mentality': 9510, 'unagi': 9511, '7elw': 9512, 'mesh': 9513, 'beyt': 9514, '3a2ad': 9515, 'fluent': 9516, 'varsity': 9517, 'sengenza': 9518, 'typos': 9519, 'movnat': 9520, 'yield': 9521, 'nbheroes': 9522, 'agover': 9523, 'brasileirao': 9524, 'abusive': 9525, 'unfollower': 9526, 'unparents': 9527, 'bianca': 9528, 'bun': 9529, 'dislike': 9530, 'burdensome': 9531, 'amelia': 9532, 'melon': 9533, 'soccer': 9534}\n"
     ]
    }
   ],
   "source": [
    "# GRADED FUNCTION: build_vocabulary\n",
    "def build_vocabulary(corpus):\n",
    "    '''Function that builds a vocabulary from the given corpus\n",
    "    Input: \n",
    "        - corpus (list): the corpus\n",
    "    Output:\n",
    "        - vocab (dict): Dictionary of all the words in the corpus.\n",
    "                The keys are the words and the values are integers.\n",
    "    '''\n",
    "\n",
    "    # The vocabulary includes special tokens like padding token and token for unknown words\n",
    "    # Keys are words and values are distinct integers (increasing by one from 0)\n",
    "    vocab = {'': 0, '[UNK]': 1} \n",
    "\n",
    "    ### START CODE HERE ###\n",
    "    \n",
    "    # For each tweet in the training set\n",
    "    for tweet in corpus:\n",
    "        # For each word in the tweet\n",
    "        for word in tweet:\n",
    "            # If the word is not in vocabulary yet, add it to vocabulary\n",
    "            if word not in vocab:\n",
    "                vocab[word] = vocab[list(vocab.keys())[-1]]+1\n",
    "    \n",
    "    ### END CODE HERE ###\n",
    "    \n",
    "    return vocab\n",
    "\n",
    "\n",
    "vocab = build_vocabulary(train_x)\n",
    "num_words = len(vocab)\n",
    "\n",
    "print(f\"Vocabulary contains {num_words} words\\n\")\n",
    "print(vocab)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e748f56",
   "metadata": {},
   "source": [
    "The dictionary `Vocab` will look like this:\n",
    "```CPP\n",
    "{'': 0,\n",
    " '[UNK]': 1,\n",
    " 'followfriday': 2,\n",
    " 'top': 3,\n",
    " 'engage': 4,\n",
    " ...\n",
    "```\n",
    "\n",
    "- Each unique word has a unique integer associated with it.\n",
    "- The total number of words in Vocab: 9535"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "afba257d",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test the build_vocabulary function\n",
    "w1_unittest.test_build_vocabulary(build_vocabulary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bfa1614",
   "metadata": {},
   "source": [
    "<a name=\"2-3\"></a>\n",
    "### 2.3 - Convert a Tweet to a Tensor\n",
    "\n",
    "Next, you will write a function that will convert each tweet to a tensor (a list of integer IDs representing the processed tweet).\n",
    "- You already transformed each tweet to a list of tokens with the `process_tweet` function in order to make a vocabulary.\n",
    "- Now you will transform the tokens to integers and pad the tensors so they all have equal length.\n",
    "- Note, the returned data type will be a **regular Python `list()`**\n",
    "    - You won't use TensorFlow in this function\n",
    "    - You also won't use a numpy array\n",
    "- For words in the tweet that are not in the vocabulary, set them to the unique ID for the token `[UNK]`.\n",
    "\n",
    "##### Example\n",
    "You had the original tweet:\n",
    "```CPP\n",
    "'@happypuppy, is Maria happy?'\n",
    "```\n",
    "\n",
    "The tweet is already converted into a list of tokens (including only relevant words).\n",
    "```CPP\n",
    "['maria', 'happy']\n",
    "```\n",
    "\n",
    "Now you will convert each word into its unique integer.\n",
    "\n",
    "```CPP\n",
    "[1, 55]\n",
    "```\n",
    "- Notice that the word \"maria\" is not in the vocabulary, so it is assigned the unique integer associated with the `[UNK]` token, because it is considered \"unknown.\"\n",
    "\n",
    "After that, you will pad the tweet with zeros so that all the tweets have the same length.\n",
    "\n",
    "```CPP\n",
    "[1, 56, 0, 0, ... , 0]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae577b59",
   "metadata": {},
   "source": [
    "First, let's have a look at the length of the processed tweets. You have to look at all tweets in the training and validation set and find the longest one to pad all of them to the maximum length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a9cc2e70",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Tweet lengths\n",
    "plt.hist([len(t) for t in train_x + val_x]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e1b006c",
   "metadata": {},
   "source": [
    "Now find the length of the longest tweet. Remember to look at the training and the validation set."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7bbe5df",
   "metadata": {},
   "source": [
    "<a name=\"ex-2\"></a>\n",
    "### Exercise 2 - max_len\n",
    "Calculate the length of the longest tweet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f7078bca",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The length of the longest tweet is 51 tokens.\n"
     ]
    }
   ],
   "source": [
    "# GRADED FUNCTION: max_length\n",
    "def max_length(training_x, validation_x):\n",
    "    \"\"\"Computes the length of the longest tweet in the training and validation sets.\n",
    "\n",
    "    Args:\n",
    "        training_x (list): The tweets in the training set.\n",
    "        validation_x (list): The tweets in the validation set.\n",
    "\n",
    "    Returns:\n",
    "        int: Length of the longest tweet.\n",
    "    \"\"\"\n",
    "    ### START CODE HERE ###\n",
    "\n",
    "    max_len = max(len(x) for x in training_x + validation_x)\n",
    "    \n",
    "    ### END CODE HERE ###\n",
    "    return max_len\n",
    "\n",
    "max_len = max_length(train_x, val_x)\n",
    "print(f'The length of the longest tweet is {max_len} tokens.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f2deac7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " ['hey',\n",
       "  'james',\n",
       "  'odd',\n",
       "  ':/',\n",
       "  'please',\n",
       "  'call',\n",
       "  'contact',\n",
       "  'centre',\n",
       "  '02392441234',\n",
       "  'able',\n",
       "  'assist',\n",
       "  ':)',\n",
       "  'many',\n",
       "  'thanks'],\n",
       " ['listen', 'last', 'night', ':)', 'bleed', 'amazing', 'track', 'scotland'],\n",
       " ['congrats', ':)'],\n",
       " ['yeaaah',\n",
       "  'yipppy',\n",
       "  'accnt',\n",
       "  'verify',\n",
       "  'rqst',\n",
       "  'succeed',\n",
       "  'get',\n",
       "  'blue',\n",
       "  'tick',\n",
       "  'mark',\n",
       "  'fb',\n",
       "  'profile',\n",
       "  ':)',\n",
       "  '15',\n",
       "  'day'],\n",
       " ['one', 'irresistible', ':)', 'flipkartfashionfriday'],\n",
       " ['like',\n",
       "  'keep',\n",
       "  'lovely',\n",
       "  'customer',\n",
       "  'wait',\n",
       "  'long',\n",
       "  'hope',\n",
       "  'enjoy',\n",
       "  'happy',\n",
       "  'friday',\n",
       "  'lwwf',\n",
       "  ':)'],\n",
       " ['second',\n",
       "  'thought',\n",
       "  '’',\n",
       "  'enough',\n",
       "  'time',\n",
       "  'dd',\n",
       "  ':)',\n",
       "  'new',\n",
       "  'short',\n",
       "  'enter',\n",
       "  'system',\n",
       "  'sheep',\n",
       "  'must',\n",
       "  'buy'],\n",
       " ['jgh', 'go', 'bayan', ':D', 'bye'],\n",
       " ['act',\n",
       "  'mischievousness',\n",
       "  'call',\n",
       "  'etl',\n",
       "  'layer',\n",
       "  'in-house',\n",
       "  'warehouse',\n",
       "  'app',\n",
       "  'katamari',\n",
       "  'well',\n",
       "  '…',\n",
       "  'name',\n",
       "  'imply',\n",
       "  ':p'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['love', 'big', '...', 'juicy', '...', 'selfies', ':)'],\n",
       " ['follow'],\n",
       " ['perfect', 'already', 'know', \"what's\", 'wait', ':)'],\n",
       " ['great',\n",
       "  'new',\n",
       "  'opportunity',\n",
       "  'junior',\n",
       "  'triathletes',\n",
       "  'age',\n",
       "  '12',\n",
       "  '13',\n",
       "  'gatorade',\n",
       "  'series',\n",
       "  'get',\n",
       "  'entry',\n",
       "  ':)'],\n",
       " ['lay', 'greeting', 'card', 'range', 'print', 'today', 'love', 'job', ':-)'],\n",
       " [\"friend's\", 'lunch', '...', 'yummm', ':)', 'nostalgia', 'tb', 'ku'],\n",
       " ['id', 'conflict', 'thanks', 'help', ':D', \"here's\", 'screenshot', 'work'],\n",
       " ['hi', 'liv', ':)'],\n",
       " ['hello',\n",
       "  'need',\n",
       "  'know',\n",
       "  'something',\n",
       "  'u',\n",
       "  'fm',\n",
       "  'twitter',\n",
       "  '—',\n",
       "  'sure',\n",
       "  'thing',\n",
       "  ':)',\n",
       "  'dm',\n",
       "  'x'],\n",
       " ['followfriday', 'top', 'new', 'follower', 'community', 'week', ':)'],\n",
       " [\"i've\",\n",
       "  'hear',\n",
       "  'four',\n",
       "  'season',\n",
       "  'pretty',\n",
       "  'dope',\n",
       "  'penthouse',\n",
       "  'obvs',\n",
       "  'gobigorgohome',\n",
       "  'fun',\n",
       "  \"y'all\",\n",
       "  ':)'],\n",
       " ['yeah', 'suppose', 'lol', 'chat', 'bit', 'x', ':)'],\n",
       " ['hello', ':)', 'get', 'youth', 'job', 'opportunity', 'follow'],\n",
       " ['💅🏽', '💋', ':)', 'see', 'year'],\n",
       " ['thank', ':-)'],\n",
       " ['hope',\n",
       "  'rest',\n",
       "  'night',\n",
       "  'go',\n",
       "  'quickly',\n",
       "  '...',\n",
       "  'bed',\n",
       "  '...',\n",
       "  'get',\n",
       "  'music',\n",
       "  'fix',\n",
       "  'time',\n",
       "  'dream',\n",
       "  ':)'],\n",
       " ['spiritual',\n",
       "  'ritual',\n",
       "  'festival',\n",
       "  'népal',\n",
       "  'beginning',\n",
       "  'line-up',\n",
       "  ':)',\n",
       "  'leave',\n",
       "  'line-up',\n",
       "  'see',\n",
       "  '...'],\n",
       " ['hey',\n",
       "  'sarah',\n",
       "  'send',\n",
       "  'u',\n",
       "  'email',\n",
       "  'bitsy@bitdefender.com',\n",
       "  \"we'll\",\n",
       "  'help',\n",
       "  'asap',\n",
       "  ':)'],\n",
       " ['lols', ':D'],\n",
       " ['kik',\n",
       "  'hatessuce',\n",
       "  '32429',\n",
       "  'kik',\n",
       "  'kikme',\n",
       "  'lgbt',\n",
       "  'tinder',\n",
       "  'nsfw',\n",
       "  'akua',\n",
       "  'cumshot',\n",
       "  ':)'],\n",
       " ['come', 'house', ':)'],\n",
       " ['nsn_supplements',\n",
       "  'effective',\n",
       "  'press',\n",
       "  'release',\n",
       "  'distribution',\n",
       "  'result',\n",
       "  ':)',\n",
       "  'link',\n",
       "  'remove',\n",
       "  'pressrelease',\n",
       "  'newsdistribution'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x46'],\n",
       " ['everyone', 'watch', 'documentary', 'earthling', 'youtube', ':-)'],\n",
       " ['follow'],\n",
       " ['followfriday', 'top', 'support', 'community', 'week', ':)'],\n",
       " ['buuut', 'oh', 'well', ':-)'],\n",
       " ['look', 'forward', 'visit', 'next', 'week', 'letsgetmessy', 'jo', ':-)'],\n",
       " ['make',\n",
       "  'u',\n",
       "  'feel',\n",
       "  'well',\n",
       "  'never',\n",
       "  'see',\n",
       "  'anyone',\n",
       "  'kpop',\n",
       "  'flesh',\n",
       "  ':D'],\n",
       " ['good', 'girl', 'best', 'wish', ':-)'],\n",
       " ['great', 'enough', 'reason', 'listen', 'one', 'epic', 'soundtrack', ':D'],\n",
       " ['thank', 'shout', 'great', 'friday', ':)'],\n",
       " ['add', 'video', 'playlist'],\n",
       " ['would', 'love', 'see', 'dear', 'jordan', ':)', 'wait', ':)'],\n",
       " ['oh', 'okay', ':D', 'thanks'],\n",
       " ['like',\n",
       "  'fake',\n",
       "  'gameplays',\n",
       "  ';)',\n",
       "  'haha',\n",
       "  'im',\n",
       "  'kidding',\n",
       "  'im',\n",
       "  'kidding',\n",
       "  'good',\n",
       "  'stuff',\n",
       "  ':)'],\n",
       " ['yeah', 'exactly', ':)'],\n",
       " ['new', 'product', 'line', 'etsy', 'shop', 'check', ':)'],\n",
       " ['hope', 'vacation', 'go', 'great', ':D'],\n",
       " ['rechargeable', 'normally', 'come', 'charger', 'u', 'buy', ':)'],\n",
       " ['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " ['well', 'asleep', 'one', 'talk', 'sooo', 'someone', 'text', ':)'],\n",
       " ['yes',\n",
       "  'suppose',\n",
       "  'bet',\n",
       "  \"he'll\",\n",
       "  'blue',\n",
       "  'fit',\n",
       "  'hear',\n",
       "  'speech',\n",
       "  'today',\n",
       "  'pity',\n",
       "  ':-)'],\n",
       " ['green',\n",
       "  'garden',\n",
       "  'midnight',\n",
       "  'sun',\n",
       "  'beautiful',\n",
       "  'canal',\n",
       "  'dasvidaniya',\n",
       "  'till',\n",
       "  'next',\n",
       "  'visit',\n",
       "  ':)'],\n",
       " ['scout', 'sg', 'future', 'wlan', 'pro', 'conference', 'asia', ':)'],\n",
       " ['good', 'u', 'good', 'change', 'lollipop', '🍭', ':)'],\n",
       " ['<3', 'u', 'nez', ':)', 'agnezmo'],\n",
       " ['follow', 'please', ':)', 'big', 'dream', ':)'],\n",
       " ['oley', ':D'],\n",
       " ['mama', 'reason', 'stand', 'strong', ':)'],\n",
       " ['follow'],\n",
       " ['oh', 'god', 'misty', 'baby', 'cute', ':D'],\n",
       " ['love', 'blue', ':)', 'flipkartfashionfriday'],\n",
       " ['woohoo', \"can't\", 'wait', ':)', 'sign', 'yet', 'still', 'think', 'mka'],\n",
       " ['liam', 'access', ':)'],\n",
       " ['welcome', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '1',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['surprise', '...', 'amazing', 'figure', ':)'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['happybirthdayemilybett',\n",
       "  ':)',\n",
       "  'wish',\n",
       "  'best',\n",
       "  'beautiful',\n",
       "  'sweet',\n",
       "  'talented',\n",
       "  'amaze',\n",
       "  '…'],\n",
       " ['2', 'plan', 'day', 'drain', 'great', ':)'],\n",
       " ['gotta', 'love', 'timezones', ':p'],\n",
       " ['parent',\n",
       "  'proud',\n",
       "  '—',\n",
       "  'lol',\n",
       "  'least',\n",
       "  ':D',\n",
       "  'maybe',\n",
       "  'sometimes',\n",
       "  'get',\n",
       "  'happy',\n",
       "  'grade',\n",
       "  'al',\n",
       "  '...'],\n",
       " ['grande', ':)'],\n",
       " ['manila_bro', 'choose', 'follow', 'twitter'],\n",
       " ['sure',\n",
       "  'let',\n",
       "  'know',\n",
       "  'around',\n",
       "  '..',\n",
       "  'side',\n",
       "  'world',\n",
       "  'eh',\n",
       "  'u',\n",
       "  'take',\n",
       "  'care',\n",
       "  ':-)'],\n",
       " ['followfriday', 'top', 'new', 'follower', 'community', 'week', ':)'],\n",
       " ['finally', 'fuck', 'weekend', ':)'],\n",
       " ['real', ':)'],\n",
       " ['thanks', ':D'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x45'],\n",
       " ['yes',\n",
       "  'join',\n",
       "  'hushedcallwithfraydoe',\n",
       "  'call',\n",
       "  'gift',\n",
       "  '<3',\n",
       "  'gotta',\n",
       "  'get',\n",
       "  ':D'],\n",
       " ['yeahhh', ':)'],\n",
       " ['dm', 'make', 'night', 'well', ':)'],\n",
       " ['join',\n",
       "  'hushedpinwithsammy',\n",
       "  'event',\n",
       "  ':D',\n",
       "  'might',\n",
       "  'get',\n",
       "  'text',\n",
       "  'day',\n",
       "  'luv',\n",
       "  'u'],\n",
       " ['would', 'really', 'appreciate', 'share', 'video', 'around', ':)'],\n",
       " ['hello', ':)', 'get', 'youth', 'job', 'opportunity', 'follow'],\n",
       " ['oh', 'wow', 'beautiful', 'tom', ':)'],\n",
       " ['love', ':)'],\n",
       " ['add', 'video', 'playlist'],\n",
       " ['followfriday', 'top', 'support', 'community', 'week', ':)'],\n",
       " ['follow'],\n",
       " ['gym', 'monday', \"can't\", 'wait', ':)', 'like'],\n",
       " ['hey', \"here's\", 'invite', 'join', 'scope', 'influencer', ':)'],\n",
       " ['friend', 'know', ':)'],\n",
       " ['wait', 'nude', ':-)'],\n",
       " ['go', 'sleep', 'u', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '1',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['birthday', 'week', 'today', ':D'],\n",
       " ['want', 't-shirt', 'cool', ':D'],\n",
       " ['haw', 'phela', 'look', 'like', 'mom', 'obviously', 'look', 'like', ':)'],\n",
       " ['prince', 'charm', 'stage', ':)', 'x'],\n",
       " ['really', 'good', 'luck', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '1',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " ['tyler', 'hipster', 'glass', ':D'],\n",
       " ['hey', 'marty', 'glad', 'see', 'twitter', ':)'],\n",
       " ['hi', 'join', 'today', ':)'],\n",
       " ['do', 'thanks', ':-)'],\n",
       " ['already', 'afternoon', 'let', 'read', 'al', 'kahfi', 'day', 'finish', ':)'],\n",
       " ['ohmyg',\n",
       "  'yaya',\n",
       "  'dub',\n",
       "  'im',\n",
       "  'do',\n",
       "  'stalk',\n",
       "  'ig',\n",
       "  'accnt',\n",
       "  '..',\n",
       "  'gondooo',\n",
       "  'moo',\n",
       "  'tologooo',\n",
       "  ':)',\n",
       "  'haha'],\n",
       " [\"here's\", 'invite', 'become', 'scope', 'influencer', ':)', 'detail'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['thanks', ':)', 'zzz', 'xx'],\n",
       " ['physiotherapy', 'friday', 'hashtag', 'today', 'custom', ':-)'],\n",
       " ['know', '💪', 'monica', 'miss', 'yeah', 'sound', 'good', ':)'],\n",
       " ['good', 'morning', 'beautiful', ':)', \"that's\", 'take'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x43'],\n",
       " ['oh',\n",
       "  'yeah',\n",
       "  'definitely',\n",
       "  'go',\n",
       "  'try',\n",
       "  'tonight',\n",
       "  ':)',\n",
       "  'take',\n",
       "  'advice',\n",
       "  'treviso'],\n",
       " ['follow'],\n",
       " ['hi',\n",
       "  'would',\n",
       "  'like',\n",
       "  'concert',\n",
       "  'let',\n",
       "  'know',\n",
       "  'city',\n",
       "  'country',\n",
       "  \"i'll\",\n",
       "  'start',\n",
       "  'work',\n",
       "  'thanks',\n",
       "  ':)'],\n",
       " ['fine', '...', 'gorgeous', 'friday', 'friend', '..', 'xo', '..', ':)'],\n",
       " ['oven',\n",
       "  'roast',\n",
       "  'garlic',\n",
       "  'olive',\n",
       "  'oil',\n",
       "  'sun',\n",
       "  'dry',\n",
       "  'tomato',\n",
       "  'dried',\n",
       "  'basil',\n",
       "  'century',\n",
       "  'tuna',\n",
       "  ':)'],\n",
       " ['right', 'back', 'atchya', 'great', 'day', 'everyone', ':)'],\n",
       " ['even', 'follow', 'back', ':-)'],\n",
       " ['future', 'almost', ':)'],\n",
       " ['followfriday', 'top', 'new', 'follower', 'community', 'week', ':)'],\n",
       " ['chance', ':)'],\n",
       " ['cheer', ':)'],\n",
       " ['go', 'po', 'ice', 'cream', ':)'],\n",
       " ['agree', '100', ':)'],\n",
       " ['hehehehe', 'thats', 'point', ':p'],\n",
       " ['next', 'time', 'stay', 'home', ':)'],\n",
       " ['thanks', ':)'],\n",
       " ['followfriday', 'top', 'support', 'community', 'week', ':)'],\n",
       " ['soon', 'promise', ':)'],\n",
       " ['web',\n",
       "  'whatsapp',\n",
       "  'volta',\n",
       "  'funcionar',\n",
       "  'com',\n",
       "  'iphone',\n",
       "  'jailbroken',\n",
       "  ':-)'],\n",
       " ['plan',\n",
       "  'watch',\n",
       "  'later',\n",
       "  '34',\n",
       "  'min',\n",
       "  'leia',\n",
       "  'appear',\n",
       "  'hologram',\n",
       "  'r2d2',\n",
       "  'w',\n",
       "  'message',\n",
       "  'obi',\n",
       "  'wan',\n",
       "  'sit',\n",
       "  'w',\n",
       "  'luke',\n",
       "  ':)'],\n",
       " ['inter', '3', 'ucl', 'arsenal', '...', 'small', 'team', 'right', ':)'],\n",
       " ['passing',\n",
       "  ':)',\n",
       "  '🚂',\n",
       "  'dewsbury',\n",
       "  'railway',\n",
       "  'station',\n",
       "  'dew',\n",
       "  'dewsbury',\n",
       "  'west',\n",
       "  'yorkshire'],\n",
       " [':)', '430', 'smh'],\n",
       " ['9:25', ':)', 'live', 'scotland', ':)', 'strange', 'imagine', 'megan', 'xx'],\n",
       " ['masaantoday',\n",
       "  'masaantoday',\n",
       "  'a4',\n",
       "  '...',\n",
       "  'shweta',\n",
       "  'tripathi',\n",
       "  'masaantoday',\n",
       "  'masaantoday',\n",
       "  ':-)',\n",
       "  '..'],\n",
       " ['5', '20', 'w', 'kurta', 'mom', 'half', 'number', ':D', 'wsalelove'],\n",
       " ['ah', 'hello', 'back', 'larry', ':)'],\n",
       " ['anyway', 'friday', 'look', 'kinda', 'goood', ':)'],\n",
       " ['follow'],\n",
       " ['lol', 'well', \"that's\", 'life', ':)', 'thank', 'god', 'enn'],\n",
       " ['surely', 'could', 'warmup', 'morning', 'come', '15th', 'bath', ':)', 'xx'],\n",
       " ['dum',\n",
       "  'dum',\n",
       "  'andar',\n",
       "  'ram',\n",
       "  'sampath',\n",
       "  'sona',\n",
       "  'mohapatra',\n",
       "  'samantha',\n",
       "  'edward',\n",
       "  'mein',\n",
       "  'tulane',\n",
       "  'razi',\n",
       "  'razi',\n",
       "  'wah',\n",
       "  \"that's\",\n",
       "  'josh',\n",
       "  ':)'],\n",
       " [':)', 'always', 'smile'],\n",
       " ['picture', ':)'],\n",
       " ['thanks', 'time', '16.20', 'right', \"that's\", 'perfect', 'timing', ':)'],\n",
       " ['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " ['know', ':)'],\n",
       " ['giveitup',\n",
       "  'already',\n",
       "  'give',\n",
       "  'gas',\n",
       "  'subsidy',\n",
       "  'long',\n",
       "  'back',\n",
       "  'initiative',\n",
       "  'propose',\n",
       "  '..',\n",
       "  'feeling',\n",
       "  'delighted',\n",
       "  'do',\n",
       "  ':)'],\n",
       " ['miss', 'yesterday', ':-)'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x42'],\n",
       " ['lmaoo',\n",
       "  'best',\n",
       "  'song',\n",
       "  'ever',\n",
       "  '<3',\n",
       "  'shall',\n",
       "  'little',\n",
       "  'throwback',\n",
       "  'week',\n",
       "  ':p'],\n",
       " ['go',\n",
       "  'outlying',\n",
       "  'island',\n",
       "  'cheung',\n",
       "  'chau',\n",
       "  'mui',\n",
       "  'wo',\n",
       "  '...',\n",
       "  'totally',\n",
       "  'different',\n",
       "  ':)'],\n",
       " ['kfckitchentours', 'kitchen', 'clean', \"i'm\", 'totally', 'amazed', ':)'],\n",
       " ['follow'],\n",
       " ['cusp', 'test', 'water', 'hope', 'reward', ':)'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['arummzz',\n",
       "  \"let's\",\n",
       "  'go',\n",
       "  '...',\n",
       "  \"i'll\",\n",
       "  'drive',\n",
       "  ':p',\n",
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       "  'yogyakarta',\n",
       "  'jeep',\n",
       "  'indonesia',\n",
       "  'instamood',\n",
       "  '…'],\n",
       " ['anyone', 'wanna', 'skype', ':D'],\n",
       " ['may', 'look', 'bit', 'real', 'nice', 'friendly', 'girl', ':-)'],\n",
       " ['im', 'like', 'pretend', ':)'],\n",
       " ['watch', 'concert', 'film', ':)'],\n",
       " ['congratulation',\n",
       "  'winner',\n",
       "  'cheesydelights',\n",
       "  'contest',\n",
       "  ':)',\n",
       "  'please',\n",
       "  'dm',\n",
       "  'u',\n",
       "  'address',\n",
       "  'contact',\n",
       "  'number'],\n",
       " [':)', 'great', 'weekend', 'guy'],\n",
       " ['followfriday', 'top', 'new', 'follower', 'community', 'week', ':)'],\n",
       " ['cool', 'see', 'film', 'today', ':)'],\n",
       " ['check', 'email', 'marketing', '24/7'],\n",
       " ['lol',\n",
       "  'come',\n",
       "  'join',\n",
       "  'u',\n",
       "  '...',\n",
       "  'see',\n",
       "  'u',\n",
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       "  '14',\n",
       "  'hour',\n",
       "  'u',\n",
       "  'leave',\n",
       "  'without',\n",
       "  'delay',\n",
       "  ':)'],\n",
       " ['actually',\n",
       "  'easy',\n",
       "  'like',\n",
       "  'must',\n",
       "  'station',\n",
       "  'guess',\n",
       "  'train',\n",
       "  'wd',\n",
       "  'take',\n",
       "  'least',\n",
       "  'hour',\n",
       "  'shift',\n",
       "  'engine',\n",
       "  'etc',\n",
       "  ':-)'],\n",
       " ['sunburn', 'peel', ':-)'],\n",
       " ['visit', 'blog'],\n",
       " ['hi',\n",
       "  'would',\n",
       "  'like',\n",
       "  'concert',\n",
       "  'let',\n",
       "  'know',\n",
       "  'city',\n",
       "  'country',\n",
       "  \"i'll\",\n",
       "  'start',\n",
       "  'work',\n",
       "  'thanks',\n",
       "  ':)'],\n",
       " ['talk', 'help', ':)'],\n",
       " ['huge',\n",
       "  'warm',\n",
       "  'welcome',\n",
       "  ':-)',\n",
       "  '☆',\n",
       "  'finally',\n",
       "  'complete',\n",
       "  'triangle',\n",
       "  '☆'],\n",
       " ['live', 'northern', 'ireland', ':)', 'sight', 'see'],\n",
       " ['follow'],\n",
       " ['followfriday', 'top', 'support', 'community', 'week', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '1',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['feel',\n",
       "  'smthng',\n",
       "  'smthng',\n",
       "  'fr',\n",
       "  'u',\n",
       "  '...',\n",
       "  'lol',\n",
       "  '...',\n",
       "  'wanna',\n",
       "  'hug',\n",
       "  'u',\n",
       "  '...',\n",
       "  'xoxo',\n",
       "  '...',\n",
       "  'love',\n",
       "  'uu',\n",
       "  'jaann',\n",
       "  'take',\n",
       "  'care',\n",
       "  ':)',\n",
       "  '<3'],\n",
       " ['thanks', 'mom', ':)'],\n",
       " ['thanks', 'topnewfollowers', 'happy', 'connect', ':)'],\n",
       " ['wonderful',\n",
       "  'thing',\n",
       "  'make',\n",
       "  'feel',\n",
       "  'fluffy',\n",
       "  'inside',\n",
       "  'great',\n",
       "  'pirouette',\n",
       "  'moose',\n",
       "  ':D'],\n",
       " ['trip', 'philly', 'december', ':)', \"i'd\", 'love', 'come', 'dude'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x41'],\n",
       " ['question', 'flaw', 'pain', 'negate', 'strength', ':)'],\n",
       " ['go', 'solo', 'move', 'make', ':D'],\n",
       " ['hey',\n",
       "  'fav',\n",
       "  'nirvana',\n",
       "  'song',\n",
       "  'smell',\n",
       "  'like',\n",
       "  'teen',\n",
       "  'spirit',\n",
       "  'rip',\n",
       "  'amy',\n",
       "  'winehouse',\n",
       "  ':-)'],\n",
       " ['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " [\"let's\",\n",
       "  'go',\n",
       "  '...',\n",
       "  \"i'll\",\n",
       "  'drive',\n",
       "  ':p',\n",
       "  'travel',\n",
       "  'traveler',\n",
       "  'yogyakarta',\n",
       "  'jeep',\n",
       "  'indonesia',\n",
       "  'instamood',\n",
       "  '…'],\n",
       " ['name',\n",
       "  'couple',\n",
       "  'yet',\n",
       "  'tomhiddleston',\n",
       "  'elizabetholsen',\n",
       "  'yaytheylookgreat',\n",
       "  ':)'],\n",
       " ['love', 'goodnight', 'vid', 'go', 'wake', 'love', 'one', ':)'],\n",
       " ['weekend',\n",
       "  'gonna',\n",
       "  'shoot',\n",
       "  'lovely',\n",
       "  '<3',\n",
       "  'picture',\n",
       "  'make',\n",
       "  'last',\n",
       "  'time',\n",
       "  ':D'],\n",
       " ['anyway', ':-)'],\n",
       " ['itty', 'bitty', 'teenie', 'bikini', ':)'],\n",
       " ['join',\n",
       "  'hushedpinwithsammy',\n",
       "  'event',\n",
       "  ':D',\n",
       "  'might',\n",
       "  'get',\n",
       "  'text',\n",
       "  'day',\n",
       "  'luv',\n",
       "  'u'],\n",
       " ['always',\n",
       "  'much',\n",
       "  'fun',\n",
       "  '4th',\n",
       "  'hour',\n",
       "  'get',\n",
       "  'together',\n",
       "  ':)',\n",
       "  'end',\n",
       "  'night',\n",
       "  'ice',\n",
       "  'cream',\n",
       "  'xfiles',\n",
       "  'content'],\n",
       " ['easy', ':D'],\n",
       " ['yes', 'surprise', 'see', 'bit', 'rain', 'today', '...', ':)'],\n",
       " ['follow'],\n",
       " ['fabulous', 'friday', 'keep', 'fantastic', 'work', ':)'],\n",
       " ['please',\n",
       "  'follow',\n",
       "  '♡',\n",
       "  '♡',\n",
       "  '♡',\n",
       "  'please',\n",
       "  'jb',\n",
       "  'follow',\n",
       "  'love',\n",
       "  'always',\n",
       "  'forever',\n",
       "  \"i'm\",\n",
       "  'belieber',\n",
       "  '♡',\n",
       "  '♡',\n",
       "  '♡',\n",
       "  ':)',\n",
       "  'love',\n",
       "  'u'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['morning', ':)'],\n",
       " ['good', 'hear', ':)'],\n",
       " ['nighty', 'night', 'let', 'bed', 'bug', 'bite', ':D'],\n",
       " ['beautiful', 'bracelet', 'good', 'idea', ':)'],\n",
       " ['wait', 'foundry', ':)'],\n",
       " ['like', 'game', ':)'],\n",
       " ['ah',\n",
       "  'make',\n",
       "  'sense',\n",
       "  '...',\n",
       "  'see',\n",
       "  'pic',\n",
       "  'eff',\n",
       "  'phone',\n",
       "  'last',\n",
       "  'night',\n",
       "  'woot',\n",
       "  ':)',\n",
       "  'x'],\n",
       " ['hi', 'derek', 'could', 'try', 'use', 'parkshare', 'gloucestershire'],\n",
       " ['aaaahhh', 'man', 'track', 'traffic', 'stress', 'reliever', ':)'],\n",
       " ['followfriday', 'top', 'new', 'follower', 'community', 'week', ':)'],\n",
       " [\"how're\", 'today', 'dear', ':)'],\n",
       " ['hear', 'guy', 'want', 'arbeloa', ':D'],\n",
       " ['turn',\n",
       "  '17',\n",
       "  '15',\n",
       "  'day',\n",
       "  '...',\n",
       "  'omg',\n",
       "  'least',\n",
       "  '3',\n",
       "  'year',\n",
       "  'difference',\n",
       "  ':)'],\n",
       " ['well', 'say', 'europe', 'rise', 'find', 'hard', 'believe', ':)'],\n",
       " ['wsalelove', 'uncountable', 'coz', 'love', 'unlimited', ':)'],\n",
       " ['yes', 'course', ':)', 'teampositive'],\n",
       " ['yes', 'love', ':-)', 'aldub'],\n",
       " [':)', '☕', '☕', '☕', 'thank', 'rita'],\n",
       " ['hi', 'could', 'please', 'dm', 'u', 'info', \"we'd\", 'happy', 'help', ':)'],\n",
       " ['way', 'boy', ':)'],\n",
       " ['hope', 'get', 'lot', 'nice', 'gift', ':D'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x40'],\n",
       " ['followfriday', 'top', 'support', 'community', 'week', ':)'],\n",
       " ['true', ':)'],\n",
       " ['add', 'video', 'playlist'],\n",
       " ['sethi', 'high', ':)'],\n",
       " ['exe', 'skeem', 'saam', ':)'],\n",
       " ['people', 'make', 'smile', ':)'],\n",
       " ['thanks', 'invite', ':)'],\n",
       " ['polite',\n",
       "  'izzat',\n",
       "  ':)',\n",
       "  'wese',\n",
       "  'trust',\n",
       "  'khawateen',\n",
       "  'k',\n",
       "  'sath',\n",
       "  'selfies',\n",
       "  'say',\n",
       "  'mana',\n",
       "  'kar',\n",
       "  'deya',\n",
       "  ':)'],\n",
       " ['thank', \"that's\", 'friday', 'evening', 'sort', ':-)'],\n",
       " ['smart', ':)'],\n",
       " [':-)', 'nice', 'hair', 'tbh'],\n",
       " ['5', 'year', ':)'],\n",
       " ['jacob', 'g', 'upgrade', ':-)'],\n",
       " ['nice', 'tee', 'man', ':)'],\n",
       " ['happy', 'family', 'vacation', '..', ':D', 'pic', '—'],\n",
       " ['sleep', 'would', 'nice', ':-)'],\n",
       " ['reading', 'beautiful', 'like', 'read', ':)'],\n",
       " ['talk', 'one', 'person', '...', 'two', 'conversation', ':)'],\n",
       " ['skype', 'fun', ':-)'],\n",
       " ['online', ':)'],\n",
       " ['...', 'friday', ':D'],\n",
       " ['followfriday', 'top', 'engage', 'member', 'community', 'week', ':)'],\n",
       " ['something',\n",
       "  'get',\n",
       "  'friday',\n",
       "  'great',\n",
       "  'start',\n",
       "  ':)',\n",
       "  'great',\n",
       "  'day',\n",
       "  'mclaren',\n",
       "  'fridayfeeling',\n",
       "  'tgif'],\n",
       " ['follow'],\n",
       " ['square', 'enix', 'bissmillah', 'ya', 'allah', ':)'],\n",
       " [\"we're\",\n",
       "  'training',\n",
       "  'socent',\n",
       "  'startup',\n",
       "  'week',\n",
       "  'w',\n",
       "  \"we'd\",\n",
       "  'love',\n",
       "  'drop',\n",
       "  'youre',\n",
       "  'arnd',\n",
       "  'town',\n",
       "  ':)'],\n",
       " ['basically', 'piss', 'cup', 'test', ':)'],\n",
       " ['next', ':)'],\n",
       " ['also', 'twitter', 'terrible', 'complicated', 'discussion', ':)'],\n",
       " ['snapchat',\n",
       "  'lynettelowe',\n",
       "  'snapchat',\n",
       "  'kikmenow',\n",
       "  'snapme',\n",
       "  'hot',\n",
       "  'snapchat',\n",
       "  'amazon',\n",
       "  'kikmeguys',\n",
       "  ':)'],\n",
       " ['look', 'forward', '12', 'hour', 'shift', 'today', ':)'],\n",
       " ['definately',\n",
       "  'agree',\n",
       "  'grow',\n",
       "  'sport',\n",
       "  'drop',\n",
       "  'email',\n",
       "  'detail',\n",
       "  'see',\n",
       "  ':-)'],\n",
       " ['last', 'rt', ':)'],\n",
       " ['...', 'rakyat', 'keep', 'visit', 'blog', 'read', 'writing', ':)'],\n",
       " ['ever',\n",
       "  'since',\n",
       "  'mention',\n",
       "  'fly',\n",
       "  'fish',\n",
       "  'day',\n",
       "  \"i'm\",\n",
       "  'get',\n",
       "  'follow',\n",
       "  'promoted',\n",
       "  'post',\n",
       "  'lol',\n",
       "  'cyber',\n",
       "  'stalk',\n",
       "  ':-)'],\n",
       " ['ourdaughtersourpride', 'mypapamypride', 'proud', 'papa', 'coach', ':)'],\n",
       " ['great', 'talk', ':D'],\n",
       " ['never',\n",
       "  'see',\n",
       "  'positive',\n",
       "  'kha',\n",
       "  'u',\n",
       "  'could',\n",
       "  'also',\n",
       "  'mention',\n",
       "  'atleast',\n",
       "  'go',\n",
       "  ':)'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x39'],\n",
       " ['mango',\n",
       "  \"lassi's\",\n",
       "  \"monty's\",\n",
       "  'marvellous',\n",
       "  ':D',\n",
       "  'though',\n",
       "  'suspect',\n",
       "  \"that's\",\n",
       "  'mean',\n",
       "  '...'],\n",
       " ['followfriday', 'top', 'influencers', 'community', 'week', ':)'],\n",
       " ['haha',\n",
       "  'yes',\n",
       "  '24',\n",
       "  'hr',\n",
       "  'time',\n",
       "  'come',\n",
       "  'touch',\n",
       "  'kepler',\n",
       "  '452b',\n",
       "  'chalna',\n",
       "  'hai',\n",
       "  ':D'],\n",
       " ['follow'],\n",
       " ['thankyou', 'pretty', ':)'],\n",
       " ['definitely', 'hazel', 'food', 'market', 'brooklyn', 'pta', ':)'],\n",
       " ['still', 'awake', ':)'],\n",
       " ['okayy', ':D'],\n",
       " ['awww', 'thank', ':)'],\n",
       " ['ha',\n",
       "  'surprise',\n",
       "  'least',\n",
       "  'okay',\n",
       "  'see',\n",
       "  'doc',\n",
       "  'afternoon',\n",
       "  'yorkshire',\n",
       "  'splendid',\n",
       "  'though',\n",
       "  ':)',\n",
       "  'xx'],\n",
       " ['spam',\n",
       "  'folder',\n",
       "  'wow',\n",
       "  'huge',\n",
       "  'amount',\n",
       "  'need',\n",
       "  'travel',\n",
       "  'nigeria',\n",
       "  'claim',\n",
       "  ':)'],\n",
       " ['rted', 'good', 'luck', ':)'],\n",
       " ['legs', 'hurt', 'bad', ':)'],\n",
       " ['get', 'mine', 'saturday', ':-)'],\n",
       " ['thaaanks', 'december', 'puhon', ':)'],\n",
       " ['happiness', ':)'],\n",
       " ['true',\n",
       "  'change',\n",
       "  'tnc',\n",
       "  'without',\n",
       "  'prior',\n",
       "  'notification',\n",
       "  'could',\n",
       "  'use',\n",
       "  'last',\n",
       "  'night',\n",
       "  ':-)'],\n",
       " [],\n",
       " ['fat', 'co', 'probably', 'eat', 'yuna', ':D', ':D', ':D'],\n",
       " ['fun', 'tameside', ':)'],\n",
       " [':-)', ':-)', ':-)'],\n",
       " ['´', 'welcome', ':)'],\n",
       " ['google', 'account', ':)'],\n",
       " ['call', 'scouser', 'everything', 'hope', 'zoe', 'well', 'mate', ':)'],\n",
       " ['right',\n",
       "  'literally',\n",
       "  'like',\n",
       "  'maybe',\n",
       "  'u',\n",
       "  'get',\n",
       "  'people',\n",
       "  'actually',\n",
       "  'know',\n",
       "  \"they're\",\n",
       "  ':-)'],\n",
       " ['sameee', 'rest', 'well', ':)'],\n",
       " ['happy',\n",
       "  'birthday',\n",
       "  'edgar',\n",
       "  'hope',\n",
       "  'good',\n",
       "  'one',\n",
       "  'keep',\n",
       "  'update',\n",
       "  'travel',\n",
       "  'log',\n",
       "  ':)'],\n",
       " ['hello', ':D'],\n",
       " ['bring', 'abes', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '2',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['someone', 'talk', ':)'],\n",
       " ['never', 'ever', 'meet', ':D'],\n",
       " ['come', 'man', ':D', ':D'],\n",
       " ['follow'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x38'],\n",
       " ['sigh', 'dreamily', 'pout', 'come', 'bath', 'eye', ':-)', 'quacketyquack'],\n",
       " ['happy', 'birthday', 'love', ':)'],\n",
       " ['cheer', ':-)'],\n",
       " ['funny', 'happen', 'phil'],\n",
       " [\"i'd\", 'call', 'em', 'del', 'rodders', ':)', 'else'],\n",
       " ['hi',\n",
       "  'may',\n",
       "  'like',\n",
       "  'play',\n",
       "  'new',\n",
       "  'gamejam',\n",
       "  'game',\n",
       "  'would',\n",
       "  'happy',\n",
       "  ':)'],\n",
       " ['great',\n",
       "  'irish',\n",
       "  'literature',\n",
       "  'really',\n",
       "  'inaccessible',\n",
       "  'u',\n",
       "  'without',\n",
       "  'irish',\n",
       "  ':)'],\n",
       " ['yeah', 'fun', ':)', 'flipkartfashionfriday'],\n",
       " ['nice', 'music', ':)', 'check'],\n",
       " ['strange', \"kareena's\", 'fan', 'know', \"kareena's\", 'fan', ':)'],\n",
       " ['hello', ':)', 'get', 'youth', 'job', 'opportunity', 'follow'],\n",
       " ['well', ':)'],\n",
       " ['cool', 'look', ':)'],\n",
       " [':)', 'beautiful'],\n",
       " [\"i'm\", 'play', 'brain', 'dot', 'braindots'],\n",
       " [\"that's\", 'fair', 'enough', ':)', 'rush', 'back', 'either'],\n",
       " ['brandi', '18', 'fb', 'drop', 'selfie', ':)', 'fun'],\n",
       " ['follow'],\n",
       " ['carnival', 'men', 'put', 'mask', 'mask', 'xavier', 'forneret', ':-)'],\n",
       " ['jennifer',\n",
       "  'check',\n",
       "  'site',\n",
       "  'u',\n",
       "  'wanna',\n",
       "  'get',\n",
       "  'free',\n",
       "  '50.000',\n",
       "  '8',\n",
       "  'ball',\n",
       "  'pool',\n",
       "  'coin',\n",
       "  'thank',\n",
       "  ':)'],\n",
       " ['beautiful', 'edit', 'trish', ':)', 'love', '♥'],\n",
       " ['gratefulness',\n",
       "  'happiness',\n",
       "  ':)',\n",
       "  'post',\n",
       "  'three',\n",
       "  'thing',\n",
       "  'grateful',\n",
       "  'today',\n",
       "  'comment'],\n",
       " ['love', 'wakeup', 'beside', 'real', 'dirty', 'dirty', 'sex', ':-)'],\n",
       " ['lmaooo', 'hot', '😤', '😤', 'like', 'louis', ':)', \"he's\", 'hot'],\n",
       " ['gonna',\n",
       "  'throw',\n",
       "  'idea',\n",
       "  'cause',\n",
       "  \"they're\",\n",
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       " ['wish', 'could', 'maybe', 'one', 'year', ':)'],\n",
       " ['hey', 'guy', ':)'],\n",
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       " ['thank', 'much', '..', 'glad', 'like', '..', ':-)'],\n",
       " ['get', 'well', 'time', ':)'],\n",
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       " ['hi', 'beautiful', 'follow', 'please', ':)'],\n",
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       "  '<3',\n",
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       " ['open', 'worldwide', ':)'],\n",
       " ['get', 'fuck', 'outta', ':D'],\n",
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       " ['really', 'look', 'vantastic', ':)'],\n",
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       " ['thank',\n",
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       "  'use',\n",
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       "  'incredibleindia'],\n",
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       " ['caught', 'first', 'salmon', 'today', ':D'],\n",
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       " ['thanks',\n",
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       " ['please', 'go', 'check', 'awesome', \"friend's\", 'stream'],\n",
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       "  'beautiful',\n",
       "  'girl',\n",
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       " ['would', 'listen', 'beat', '1', 'go', 'wrong', 'life', ':)'],\n",
       " ['haha', \"that's\", 'great', ':)'],\n",
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       "  'workshop',\n",
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       "  'covent',\n",
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       "  'tomorrow',\n",
       "  ':)'],\n",
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       " ['americano', ':)'],\n",
       " [':-)'],\n",
       " ['love', 'way', ':)', '<3'],\n",
       " ['always', 'remember', ':)'],\n",
       " ['aww', 'thank', 'beautiful', 'pic', ':D'],\n",
       " ['head', ':)'],\n",
       " ['hi', 'saw', 'u', 'follow', 'think', 'u', 'might', 'like', 'dark'],\n",
       " ['smart', 'handshome', 'cute', 'juga', ':D'],\n",
       " ['hurray', 'look', 'forward', 'meeting', ':)'],\n",
       " ['follow'],\n",
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       "  'im',\n",
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       "  'time',\n",
       "  'save',\n",
       "  'maybe',\n",
       "  'travel',\n",
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       " ['list', \"i'm\", 'still', 'show', ':)'],\n",
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       "  'let',\n",
       "  'know',\n",
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       "  'country',\n",
       "  \"i'll\",\n",
       "  'start',\n",
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       "  'thanks',\n",
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       " ['oh', 'awesome', 'thank', 'much', ':)'],\n",
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       "  'web',\n",
       "  'exec',\n",
       "  'loryn.good@lincs-chamber.co.uk',\n",
       "  'able',\n",
       "  'help',\n",
       "  ':)'],\n",
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       " ['big', 'thx', '4', 'kind', 'support', 'good', 'luck', ':-)'],\n",
       " ['china',\n",
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       "  'love',\n",
       "  'either',\n",
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       "  ':D',\n",
       "  'hyungbot'],\n",
       " ['cause', 'like', 'lot', ':)'],\n",
       " ['give', 'time', 'fam', 'get', 'thing', 'mind', ':-)'],\n",
       " ['thanks', 'god', 'friday', ':)', 'jgh'],\n",
       " ['lovely', ':)'],\n",
       " ['timetunnel', '1982', 'quite', 'sure', 'radio', 'set', 'heart', ':)'],\n",
       " ['hiii', 'jack', ':)', 'ily', '✨', '✨', '✨'],\n",
       " ['play', 'domino', 'pub', 'get', 'quite', 'heat', 'enjoy', 'though', ':D'],\n",
       " ['prob', ':)'],\n",
       " ['enjoy', 'sorry', 'hastily', 'type', 'message', ':)'],\n",
       " ['ff', 'thank', ':-)'],\n",
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       " ['true', 'pakistani', ':p'],\n",
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       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x36'],\n",
       " ['3points', 'dreamteam', 'gooo', 'bailey', ':)', 'pbb', '737gold'],\n",
       " ['thank', ':)'],\n",
       " ['drink', ':)'],\n",
       " ['old', 'pic', ':)'],\n",
       " ['follow'],\n",
       " ['get', 'sleep', '3', '1/2', 'hour', ':)'],\n",
       " ['welsh', 'wale', 'today', 'yippee', ':-)'],\n",
       " ['do', ':)'],\n",
       " ['happy', 'birthday', 'baby', '💟', '💟', 'miss', 'much', 'love', 'much', ':)'],\n",
       " ['thanks', 'bro', ':D', 'x'],\n",
       " ['thats', 'lord', ':)'],\n",
       " ['sweet', ':)'],\n",
       " ['like', 'michael', ':)', 'thanks', 'kind', 'word', 'cheer', 'em'],\n",
       " ['morning',\n",
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       "  'amazing',\n",
       "  'night'],\n",
       " ['wait', 'people', 'call', 'bigot', ':p'],\n",
       " ['usually', ':)', 'front', 'back', 'squat'],\n",
       " ['much',\n",
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       "  'hope',\n",
       "  'next',\n",
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       "  'new',\n",
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       "  'musicology',\n",
       "  '2015',\n",
       "  'day',\n",
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       " ['look',\n",
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       "  'great',\n",
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       "  'afternoon',\n",
       "  'enjoy',\n",
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       " ['officially', 'graduate', ':D'],\n",
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       " ['thanks', ':)'],\n",
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       " ['minal', 'aidzin', 'yo', 'pi', ':D'],\n",
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       "  'really',\n",
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       "  'song',\n",
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       " ['welcome', '...', ':-)', ':-)'],\n",
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       "  'player',\n",
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       "  'account',\n",
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       "  'saw',\n",
       "  'best',\n",
       "  'thing',\n",
       "  'ever',\n",
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       " ['new', 'user', ':-)'],\n",
       " ['welcome', 'back', 'teamred', ':)'],\n",
       " ['oh',\n",
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       "  \"i'm\",\n",
       "  'already',\n",
       "  'member',\n",
       "  'lol',\n",
       "  'hopefully',\n",
       "  'able',\n",
       "  'come',\n",
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       "  'time',\n",
       "  ':D'],\n",
       " ['greatly', 'appreciate', ':)'],\n",
       " ['hi', 'make', 'change', 'design', 'hope', 'like', ':)'],\n",
       " ['ahhh', 'yes', ':D'],\n",
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       "  'video',\n",
       "  'festival',\n",
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       "  'mechanic',\n",
       "  'official',\n",
       "  'entry',\n",
       "  'form',\n",
       "  'may',\n",
       "  'download'],\n",
       " ['hello', ':)', 'get', 'youth', 'job', 'opportunity', 'follow'],\n",
       " ['follow'],\n",
       " ['ur', 'mom', 'get', 'u', 'swishers', 'ur', 'cop', 'monday', ':)'],\n",
       " ['song', 'week', 'ducktails', 'surreal', 'exposure', 'sotw'],\n",
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       "  'tomorrow',\n",
       "  'follower',\n",
       "  'go',\n",
       "  'come',\n",
       "  'say',\n",
       "  'hello',\n",
       "  'stand',\n",
       "  'high',\n",
       "  'street',\n",
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       " ['good', 'luck', 'assessment', 'today', ':)'],\n",
       " ['mental', 'strength', ':D'],\n",
       " ['look', 'beautiful', 'amazing', 'body', 'ooze', 'sex', 'appeal', ':)', 'xx'],\n",
       " ['home',\n",
       "  'amassiveoverdoseofships',\n",
       "  'late',\n",
       "  'vid',\n",
       "  'way',\n",
       "  '..',\n",
       "  'enjoy',\n",
       "  'visit',\n",
       "  'site',\n",
       "  '..',\n",
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       " ['isi', 'chan', ':D'],\n",
       " ['c', 'note', ':)', 'pkwalasawaal'],\n",
       " ['stats',\n",
       "  'day',\n",
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       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
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       "  'via'],\n",
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       " ['fever',\n",
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       "  'obamainkenya',\n",
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       "  ':-)',\n",
       "  'greatkenya',\n",
       "  'allgoodthingske'],\n",
       " ['funny', 'next', 'anime', 'umaru', ':D'],\n",
       " ['great', 'singer', ':)'],\n",
       " ['follow'],\n",
       " ['look', 'like', 'game', 'ship', 'u', 'get', 'order', ':)'],\n",
       " ['take', 'room', 'car', \"i'm\", 'go', 'cool', ':)'],\n",
       " ['go', 'stream', 'soon', ':)'],\n",
       " ['thanks', ':)'],\n",
       " ['hi',\n",
       "  'would',\n",
       "  'like',\n",
       "  'concert',\n",
       "  'let',\n",
       "  'know',\n",
       "  'city',\n",
       "  'country',\n",
       "  \"i'll\",\n",
       "  'start',\n",
       "  'work',\n",
       "  'thanks',\n",
       "  ':)'],\n",
       " ['hahaha',\n",
       "  'everyone',\n",
       "  'fun',\n",
       "  'story',\n",
       "  'relate',\n",
       "  'song',\n",
       "  'get',\n",
       "  'label',\n",
       "  'bad',\n",
       "  'batch',\n",
       "  'principal',\n",
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       "  ':p'],\n",
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       "  'like',\n",
       "  'march',\n",
       "  'release',\n",
       "  'one',\n",
       "  'first',\n",
       "  'start',\n",
       "  'new',\n",
       "  'one',\n",
       "  ':)'],\n",
       " ['ff', 'top', 'twoofs', 'wooftastic', 'wkend', 'guy', ':)'],\n",
       " ['well', 'receive', 'necessary', ':)'],\n",
       " ['long', 'time', 'see', ':/', ':p'],\n",
       " [\"i'll\", 'regret', 'rn', 'tomorrow', 'morning', 'whatever', ':)'],\n",
       " ['hat', ':D'],\n",
       " ['thank', ':)'],\n",
       " ['never', 'love', 'life', 'success', ':)'],\n",
       " ['abstinence', ':)'],\n",
       " ['wtf',\n",
       "  'never',\n",
       "  'happen',\n",
       "  'moment',\n",
       "  'may',\n",
       "  'may',\n",
       "  'like',\n",
       "  \"there's\",\n",
       "  'surprise',\n",
       "  'thrown',\n",
       "  ':D'],\n",
       " ['start', 'middle', 'finish', ':)'],\n",
       " ['im', 'back', 'twitter', '..', ':-)'],\n",
       " ['end', 'happy', ':)'],\n",
       " ['lovely',\n",
       "  'stuff',\n",
       "  'need',\n",
       "  'repeat',\n",
       "  'relentlessly',\n",
       "  'approximately',\n",
       "  'next',\n",
       "  '5',\n",
       "  'year',\n",
       "  ':)'],\n",
       " ['hug', 'many', ':)'],\n",
       " ['oldschool', 'runescape', ':)'],\n",
       " ['thanks', 'shout', 'wonderful', 'weekend', ':)'],\n",
       " ['rest', 'day', ':)'],\n",
       " ['lovely', 'daaay', ':D'],\n",
       " ['jumma_mubarik',\n",
       "  '<3',\n",
       "  '<3',\n",
       "  '<3',\n",
       "  'frnds',\n",
       "  'stay_blessed',\n",
       "  ':)',\n",
       "  ':)',\n",
       "  '—',\n",
       "  'feeling',\n",
       "  'bless'],\n",
       " ['sense', ':)'],\n",
       " ['awww', 'pussycats', ':-)', 'xx'],\n",
       " ['hope', 'everything', 'go', 'great', ':-)', 'lol'],\n",
       " ['market', 'main', 'launch', 'pretoria', ':)'],\n",
       " ['care',\n",
       "  'care',\n",
       "  '...',\n",
       "  'fahrinahmad',\n",
       "  'tengkuaaronshah',\n",
       "  'eksperimencinta',\n",
       "  ':D'],\n",
       " ['tykkäsin', 'videosta'],\n",
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       "  'wait',\n",
       "  'finally',\n",
       "  'hoodie',\n",
       "  ':)',\n",
       "  'eeep',\n",
       "  'yay',\n",
       "  'sohappyrightnow'],\n",
       " ['mmm', 'c', 'lovely', 'azz-sets', 'babe', ':-)'],\n",
       " ['thx', 'feedback', 'glad', 'gain', 'value', ':)'],\n",
       " ['good',\n",
       "  'night',\n",
       "  'lovely',\n",
       "  'hope',\n",
       "  'peaceful',\n",
       "  'night',\n",
       "  'rest',\n",
       "  'feel',\n",
       "  'refresh',\n",
       "  'wake',\n",
       "  'sweet',\n",
       "  'dream',\n",
       "  ':)'],\n",
       " [\"i'll\", 'never', 'get', 'use', 'thank', 'much', ':)'],\n",
       " ['thanks', 'manthan', 'stay', 'tune', 'u', ':)'],\n",
       " ['freshness',\n",
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       "  'smile',\n",
       "  'mother',\n",
       "  'determination',\n",
       "  'make',\n",
       "  'day',\n",
       "  ':)',\n",
       "  'maxfreshmove'],\n",
       " [\"i'm\", 'play', 'brain', 'dot', 'braindots'],\n",
       " ['please',\n",
       "  'james',\n",
       "  'think',\n",
       "  'beautiful',\n",
       "  'girl',\n",
       "  'lonely',\n",
       "  'tattoo',\n",
       "  'change',\n",
       "  'life',\n",
       "  ':)'],\n",
       " ['hi',\n",
       "  'girl',\n",
       "  ':)',\n",
       "  'wish',\n",
       "  'happy',\n",
       "  'friday.and',\n",
       "  'magnificent',\n",
       "  'fantastic',\n",
       "  'w',\n",
       "  'e',\n",
       "  '♡',\n",
       "  '♥',\n",
       "  '♡',\n",
       "  '♥'],\n",
       " ['achieve',\n",
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       "  'thank',\n",
       "  'rashmi',\n",
       "  'time',\n",
       "  'dedication',\n",
       "  'complete',\n",
       "  'inspiration',\n",
       "  ':)'],\n",
       " ['ff', 'happyfriday', 'weekend', 'nearly', ':-)'],\n",
       " ['retweeted', ':)'],\n",
       " ['update', 'soon', \"i'm\", 'sure', 'sign', 'set', 'text', 'alert', ':)', 'da'],\n",
       " ['something', 'new', ':D'],\n",
       " ['dang', 'rad', 'fanart', ':D'],\n",
       " ['cheer', 'tgif', ':-)'],\n",
       " ['massive',\n",
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       "  'niamh',\n",
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       "  ':)',\n",
       "  'journalism',\n",
       "  'graduate',\n",
       "  'land',\n",
       "  'dream',\n",
       "  'job',\n",
       "  'copying',\n",
       "  'paste',\n",
       "  'tweet'],\n",
       " ['thank', ':)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '5',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
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       " ['yes', 'thank', ':D'],\n",
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       "  'gomez',\n",
       "  'louis',\n",
       "  'tomlinson',\n",
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       "  'liam',\n",
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       "  '🌷',\n",
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       "  'solo',\n",
       "  'dm',\n",
       "  ':)'],\n",
       " ['tire', 'fine', ':)'],\n",
       " ['nope', 'definitely', 'still', 'apply', 'year', 'want', ':D', 'iamca'],\n",
       " ['ah', 'find', 'thanks', ':)'],\n",
       " ['aftie', ':p'],\n",
       " ['goodmorning', ':)'],\n",
       " ['follow'],\n",
       " ['’', 'exactly', 'look', '’', 'go', ':D'],\n",
       " ['prokabaddi',\n",
       "  'koel',\n",
       "  'mallick',\n",
       "  'recite',\n",
       "  'national',\n",
       "  'anthem',\n",
       "  'day',\n",
       "  '6',\n",
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       "  'youngnaturalleaders',\n",
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       "  'flockstars',\n",
       "  'thur',\n",
       "  '30july',\n",
       "  'itv'],\n",
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       " ['one',\n",
       "  'leg',\n",
       "  'september',\n",
       "  'perhaps',\n",
       "  'bb',\n",
       "  'promote',\n",
       "  'full',\n",
       "  'album',\n",
       "  'september',\n",
       "  ':D'],\n",
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       "  'intend',\n",
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       "  'many',\n",
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       "  'design',\n",
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       "  'attack',\n",
       "  'plan',\n",
       "  'next',\n",
       "  '6',\n",
       "  'month',\n",
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       " ['bird', 'come', 'join', 'u', 'little', 'fun', ':)', 'teamadmicro'],\n",
       " ['fridaydownpour', 'hope', 'clear', 'wkend', 'good', 'one', ':)'],\n",
       " ['time', 'sleep', ':)'],\n",
       " [\"that's\", 'three', 'word', \"that's\", 'rohit', ':D'],\n",
       " ['gorgeous', 'queen', '...', 'god', ':)'],\n",
       " ['long', 'wait', ':)', 'otwolgrandtrailer'],\n",
       " ['get',\n",
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       "  'sheer',\n",
       "  'fact',\n",
       "  'obama',\n",
       "  'beat',\n",
       "  'innumerable',\n",
       "  'odds',\n",
       "  'become',\n",
       "  'u',\n",
       "  'president',\n",
       "  'ni',\n",
       "  'shauri',\n",
       "  'yako',\n",
       "  ':-)',\n",
       "  'memotohaters'],\n",
       " ['everyone', 'go', 'drop', 'follow', 'stream', ':D'],\n",
       " ['happy',\n",
       "  'birthday',\n",
       "  'sunday',\n",
       "  ':)',\n",
       "  'hope',\n",
       "  'great',\n",
       "  'day',\n",
       "  'lot',\n",
       "  'pamper',\n",
       "  'love'],\n",
       " [\"t'was\", 'great', 'thank', ':)'],\n",
       " [\"i'm\",\n",
       "  'go',\n",
       "  'cabincrew',\n",
       "  'interview',\n",
       "  'langkawi',\n",
       "  '1st',\n",
       "  'august',\n",
       "  ':)',\n",
       "  'please',\n",
       "  'wish',\n",
       "  'luck'],\n",
       " ['thank', ':D'],\n",
       " ['fulfil', 'fantasy', ':)', '👉'],\n",
       " ['cool', 'thanks', 'thinking', 'hope', 'well', ':-)'],\n",
       " ['follow'],\n",
       " ['thank', 'much', 'babe', ':D'],\n",
       " ['5', 'ex-twelebs', 'side', 'please', ':)'],\n",
       " ['thanks', 'bro', ':D', 'x'],\n",
       " ['great', 'day', ':D'],\n",
       " ['make', 'much', 'sense', ':D', 'lol'],\n",
       " ['..', 'wait', ':)'],\n",
       " ['ff', 'great', 'weekend', ':)'],\n",
       " ['family', 'friends', ':)'],\n",
       " ['apartment', 'makeover'],\n",
       " ['thanks', 'welcome', 'hope', 'go', 'brilliantly', ':)'],\n",
       " ['happyyy', 'birthdaaayyy', ':-)'],\n",
       " ['come', 'kill', ':)'],\n",
       " ['hi',\n",
       "  'im',\n",
       "  'interested',\n",
       "  'internship',\n",
       "  'program',\n",
       "  'sadly',\n",
       "  'cant',\n",
       "  'access',\n",
       "  'career',\n",
       "  'page',\n",
       "  'u',\n",
       "  'help',\n",
       "  'issue',\n",
       "  ':)'],\n",
       " ['sad',\n",
       "  'hear',\n",
       "  'thank',\n",
       "  'much',\n",
       "  'overwhelmingly',\n",
       "  'beautiful',\n",
       "  'game',\n",
       "  'thank',\n",
       "  'hard',\n",
       "  'work',\n",
       "  ':)'],\n",
       " ['aha', 'yes', 'look', 'forward', 'see', ':)'],\n",
       " ['happy', 'friday', 'beauts', ':)', '♬', 'ff'],\n",
       " ['love', 'help'],\n",
       " ['would',\n",
       "  'love',\n",
       "  'win',\n",
       "  'deo',\n",
       "  'faaabulous',\n",
       "  ':D',\n",
       "  'freebiefriday',\n",
       "  'aluminiumfree',\n",
       "  'stayfresh',\n",
       "  'xx'],\n",
       " ['yes', 'john', ':)'],\n",
       " ['thanks', 'worry', \"i'll\", 'navigate', 'blog', 'check', ':)'],\n",
       " ['thnks', 'progrmr', ':-)'],\n",
       " ['bet',\n",
       "  'well',\n",
       "  'get',\n",
       "  'sleep',\n",
       "  '9pm',\n",
       "  'shift',\n",
       "  '9am',\n",
       "  'quit',\n",
       "  'hard',\n",
       "  'work',\n",
       "  'thank',\n",
       "  ':)',\n",
       "  'xx'],\n",
       " ['figure', ':-)'],\n",
       " ['hardly',\n",
       "  'surprising',\n",
       "  'roses',\n",
       "  'inspire',\n",
       "  'much',\n",
       "  'emotive',\n",
       "  'poetry',\n",
       "  ':)'],\n",
       " ['follow', ':)'],\n",
       " ['join', 'frequentflyer', 'program', ':)'],\n",
       " ['always', 'end', 'break', 'apologize', 'fuck', 'nice', ':-)'],\n",
       " ['fabulous', 'well', 'hope', 'great', 'day', ':-)', 'kb'],\n",
       " ['hi',\n",
       "  'would',\n",
       "  'like',\n",
       "  'concert',\n",
       "  'let',\n",
       "  'know',\n",
       "  'city',\n",
       "  'country',\n",
       "  \"i'll\",\n",
       "  'start',\n",
       "  'work',\n",
       "  'thanks',\n",
       "  ':)'],\n",
       " ['welcome', ':)'],\n",
       " ['visit', 'blog'],\n",
       " ['enjoy', 'londondairy', 'icecream', 'share', 'u', 'experience', ':)'],\n",
       " ['follow'],\n",
       " ['luv', 'ur', ':-)'],\n",
       " ['past', 'hoodie', 'cover', 'lot', 'sin', ':)'],\n",
       " ['bet',\n",
       "  'excited',\n",
       "  ':)',\n",
       "  \":')\",\n",
       "  'xxx',\n",
       "  'good',\n",
       "  'luck',\n",
       "  'hope',\n",
       "  'get',\n",
       "  'number',\n",
       "  'one'],\n",
       " ['welcome',\n",
       "  'jim',\n",
       "  'make',\n",
       "  'chuckle',\n",
       "  'train',\n",
       "  'morning',\n",
       "  ':-)',\n",
       "  'happy',\n",
       "  'friday'],\n",
       " ['shopping', 'bit', ':p'],\n",
       " ['agree', 'haha', ':p'],\n",
       " ['happy', 'birthday', \"we're\", 'positive', 'full', 'cake', ':)'],\n",
       " ['doh',\n",
       "  '500',\n",
       "  'subscriber',\n",
       "  'need',\n",
       "  ':)',\n",
       "  'please',\n",
       "  'let',\n",
       "  'u',\n",
       "  'know',\n",
       "  'reach',\n",
       "  'number'],\n",
       " [\"i'm\", 'good', 'thanks', 'hope', 'well', ':-)', 'xx'],\n",
       " ['dry', 'hot', 'scorch', 'summer', 'ff', ':)'],\n",
       " ['maybe', 'young', 'woman', 'stamen', 'tom', ':)'],\n",
       " ['thing',\n",
       "  'look',\n",
       "  'great',\n",
       "  'either',\n",
       "  'expect',\n",
       "  'anything',\n",
       "  'less',\n",
       "  'lol',\n",
       "  'least',\n",
       "  'weekend',\n",
       "  ':)'],\n",
       " ['finally', 'get', 'bed', ':)', 'good', 'night', 'tweeties'],\n",
       " ['thanks', 'guy', ':)'],\n",
       " ['fab', 'thank', 'support', ':)'],\n",
       " ['really', 'dont', 'love', 'much', ':)'],\n",
       " ['ff', 'follow', '-->', '10', 'loner', 'side', 'please', ':)'],\n",
       " ['charger', ':)'],\n",
       " [':-)'],\n",
       " ['introduce',\n",
       "  'new',\n",
       "  'word',\n",
       "  'v',\n",
       "  'alter',\n",
       "  'understanding',\n",
       "  'word',\n",
       "  'x',\n",
       "  'spread',\n",
       "  'either',\n",
       "  'big',\n",
       "  'problem',\n",
       "  ':)'],\n",
       " ['follow'],\n",
       " ['ff', 'wooftastic', 'twoofs', 'hope', 'supa', 'dupa', 'weekend', ':)'],\n",
       " ['near', 'enough', 'dartmoor', ':)'],\n",
       " [\"i'm\",\n",
       "  'gonna',\n",
       "  'stay',\n",
       "  'gold',\n",
       "  'colour',\n",
       "  'hopefully',\n",
       "  'come',\n",
       "  'soon',\n",
       "  'thank',\n",
       "  'anyway',\n",
       "  ':)'],\n",
       " ['follow', 'back', ':)'],\n",
       " ['yay', 'ok', ':D'],\n",
       " ['someday', \"we'll\", 'know', ':)'],\n",
       " ['u', 'r', 'dii', 'n', 'cant', 'forget', 'si', ':)'],\n",
       " ['jgh', 'fr', 'smf', 'ft', 'w', 'girl', '<3', ':)'],\n",
       " ['maybe',\n",
       "  'get',\n",
       "  'japanese',\n",
       "  'import',\n",
       "  'hello',\n",
       "  'kitty',\n",
       "  'matching',\n",
       "  'stationary',\n",
       "  ':)'],\n",
       " ['weekend', 'draw', 'close', 'plan', ':D'],\n",
       " ['hi', 'saw', 'u', 'follow', 'think', 'u', 'might', 'like', 'dark'],\n",
       " ['hello', 'twitter', 'account', 'break', ':)'],\n",
       " ['hi',\n",
       "  'thanks',\n",
       "  'connect',\n",
       "  'specialise',\n",
       "  'thermal',\n",
       "  'image',\n",
       "  'survey',\n",
       "  '–',\n",
       "  'need',\n",
       "  'u',\n",
       "  ':)'],\n",
       " ['nice', ':)'],\n",
       " ['please', 'follow', 'back', ':)', 'x', '10'],\n",
       " ['hi', 'want', 'get', 'connect', ':)', 'plan', 'come', 'south', 'korea'],\n",
       " ['oh', 'fact', ':p'],\n",
       " [\"i'd\",\n",
       "  'plan',\n",
       "  'nice',\n",
       "  'scamper',\n",
       "  'sleep',\n",
       "  'alarm',\n",
       "  'two',\n",
       "  'hour',\n",
       "  'suppose',\n",
       "  'need',\n",
       "  'sleep',\n",
       "  \"ain't\",\n",
       "  'mad',\n",
       "  ':)'],\n",
       " ['chweina',\n",
       "  '...',\n",
       "  'xd',\n",
       "  'jotzh',\n",
       "  ':D',\n",
       "  'dude',\n",
       "  '...',\n",
       "  'go',\n",
       "  'school',\n",
       "  'waste',\n",
       "  'time',\n",
       "  'twitter'],\n",
       " ['hiya',\n",
       "  'yep',\n",
       "  'show',\n",
       "  'take',\n",
       "  'place',\n",
       "  'completely',\n",
       "  'cover',\n",
       "  'worth',\n",
       "  'bring',\n",
       "  'coat',\n",
       "  'beforehand',\n",
       "  'tho',\n",
       "  'foh',\n",
       "  'outside',\n",
       "  ':-)'],\n",
       " ['thanks', ':)'],\n",
       " ['enjoy', 'holiday', ':D'],\n",
       " ['see', 'many', 'menace', 'since', 'finish', 'jojo', ':D'],\n",
       " ['ta', ':)'],\n",
       " ['thank',\n",
       "  'always',\n",
       "  'last',\n",
       "  '’',\n",
       "  'back',\n",
       "  'track',\n",
       "  ':)',\n",
       "  'hope',\n",
       "  'fantastic',\n",
       "  'weekend',\n",
       "  ':)'],\n",
       " ['make', 'good', 'though', ':-)'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '1',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['accepted', ':)'],\n",
       " ['follow'],\n",
       " ['go', 'guys', 'hope', 'enjoy', 'update', ':)', 'bye', 'admin', 'lukris'],\n",
       " ['lovely', 'day', 'yes', 'stay', 'happy', ':)', '😘'],\n",
       " ['day', ':)'],\n",
       " ['happy',\n",
       "  'birthday',\n",
       "  'momma',\n",
       "  'bear',\n",
       "  'love',\n",
       "  'much',\n",
       "  '❤',\n",
       "  '️',\n",
       "  'redo',\n",
       "  'find',\n",
       "  'last',\n",
       "  'picture',\n",
       "  '8th',\n",
       "  'grade',\n",
       "  ':)'],\n",
       " ['k', \"i'll\", 'text', 'tomorrow', ':-)'],\n",
       " ['im', ':)', 'x'],\n",
       " ['love', 'u', ':p'],\n",
       " ['nice', 'line', ':-)', ':-)'],\n",
       " ['play', 'v.ball', 'atm', ':)'],\n",
       " ['appreciate', 'recent', 'retweets', 'great', 'friday', ':)'],\n",
       " ['follow'],\n",
       " ['build',\n",
       "  'product',\n",
       "  'like',\n",
       "  'pack',\n",
       "  'suitcase',\n",
       "  'plan',\n",
       "  'think',\n",
       "  'need',\n",
       "  'remove',\n",
       "  'half',\n",
       "  'fully',\n",
       "  'agree',\n",
       "  ':)'],\n",
       " ['hang-copying', 'translation', \"dostoevsky's\", 'note', '..', ':)'],\n",
       " ['voucher', '...', 'new', 'bugatti', \"what's\", 'value', ':D'],\n",
       " ['someone', 'love', 'promise', ':)'],\n",
       " ['know', 'bra', 'know', 'bra', 'get', ':D'],\n",
       " ['مطعم_هاشم',\n",
       "  'yummy',\n",
       "  ':-)',\n",
       "  'a7la',\n",
       "  'bdayt',\n",
       "  'season',\n",
       "  ':-)',\n",
       "  'mnwreeen',\n",
       "  ':-)',\n",
       "  ':-)'],\n",
       " ['listen', 'jazz', 'truck', ':)'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x34'],\n",
       " [\"can't\", 'wait', 'speak', 'pbevent', 'see', ':)'],\n",
       " ['wait',\n",
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       "  'pic',\n",
       "  'today',\n",
       "  'add',\n",
       "  'yoona',\n",
       "  'x',\n",
       "  'hairpin',\n",
       "  'otp',\n",
       "  'collection',\n",
       "  ':D'],\n",
       " ['mastership', 'honey', ':D'],\n",
       " ['paindo', 'want', 'say', 'follow', ':p'],\n",
       " ['sure', ':)'],\n",
       " ['awesome', 'await', 'report', ':D'],\n",
       " ['throwback', 'lol', 'manny', 'still', 'asshole', ':)'],\n",
       " ['brijresidency',\n",
       "  'g',\n",
       "  '6',\n",
       "  'story',\n",
       "  'structure',\n",
       "  '156',\n",
       "  'unit',\n",
       "  'encompass',\n",
       "  '2',\n",
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       "  'bhk',\n",
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       "  ':D',\n",
       "  '91',\n",
       "  '975-580-',\n",
       "  '444'],\n",
       " ['honor', ':-)'],\n",
       " ['know', 'like', ':D'],\n",
       " ['follow'],\n",
       " ['curry', 'close', 'home', ':)'],\n",
       " ['clash', ':)', 'milano', 'call', '👌'],\n",
       " ['followback', 'po', ':-)', ':-D'],\n",
       " ['legit', 'loser', 'sit', 'get', 'gas', ':)'],\n",
       " ['friend',\n",
       "  'hi',\n",
       "  'saw',\n",
       "  'dead',\n",
       "  'thing',\n",
       "  'make',\n",
       "  'think',\n",
       "  'aww',\n",
       "  'thanks',\n",
       "  'guy',\n",
       "  ':D'],\n",
       " ['speak', ':-)'],\n",
       " ['always', ':)'],\n",
       " ['starsquad', '⭐', 'please', 'get', 'follow', 'awesome', ':)'],\n",
       " ['awww', 'thanks', ':-)'],\n",
       " ['thanks', 'news', 'man', ':)', 'utc'],\n",
       " ['remember',\n",
       "  'one',\n",
       "  'time',\n",
       "  'go',\n",
       "  'flume',\n",
       "  'kaytranada',\n",
       "  'alunageorge',\n",
       "  'even',\n",
       "  'though',\n",
       "  'ticket',\n",
       "  'still',\n",
       "  'want',\n",
       "  'kms'],\n",
       " ['oh', 'good', 'haha', 'let', 'know', 'think', ':)'],\n",
       " ['thanks',\n",
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       "  'give',\n",
       "  'certainty',\n",
       "  'problem',\n",
       "  ':)',\n",
       "  'hope',\n",
       "  'u',\n",
       "  'could',\n",
       "  'solve',\n",
       "  'faster',\n",
       "  '👊',\n",
       "  'least',\n",
       "  'know',\n",
       "  'dont',\n",
       "  'hurry',\n",
       "  '4',\n",
       "  'totem'],\n",
       " ['somewhere', 'later', ':)'],\n",
       " ['good', 'advice', 'friday', ':)'],\n",
       " ['cheer', 'alice', ':)'],\n",
       " ['go'],\n",
       " ['two',\n",
       "  'dog',\n",
       "  'one',\n",
       "  'cat',\n",
       "  'good',\n",
       "  'friend',\n",
       "  ':-)',\n",
       "  'goodwynsgoodies',\n",
       "  'freebiefriday'],\n",
       " ['ugh', \"i've\", 'never', 'rt', 'fade', 'moan', 'leeds', 'tweet', ':)'],\n",
       " ['look', 'forward', 'jozi', 'guy', ':)'],\n",
       " ['hello', ':D', 'find', 'time', 'wasnt', 'follow', 'till'],\n",
       " ['think', 'fifth', 'album', 'im', ':)', 'okay', ':)', 'fuck', ':)'],\n",
       " ['may',\n",
       "  'available',\n",
       "  'tix',\n",
       "  'pa',\n",
       "  'ba',\n",
       "  'ng',\n",
       "  'atl',\n",
       "  'concert',\n",
       "  'thanks',\n",
       "  ':)'],\n",
       " ['yeah',\n",
       "  '20',\n",
       "  'coldplay',\n",
       "  'song',\n",
       "  'playlist',\n",
       "  ':p',\n",
       "  'love',\n",
       "  'favorite',\n",
       "  'scientist',\n",
       "  'fix',\n",
       "  'yellow',\n",
       "  'atlas',\n",
       "  ':p'],\n",
       " ['awesome', ':)', \"i'll\", 'wait'],\n",
       " ['follow'],\n",
       " ['do', 'yein', ':)'],\n",
       " ['haha',\n",
       "  'receive',\n",
       "  'ff',\n",
       "  'thing',\n",
       "  'friday',\n",
       "  'nice',\n",
       "  'way',\n",
       "  'start',\n",
       "  'day',\n",
       "  ':)',\n",
       "  'xx'],\n",
       " ['lol', 'selos', ':)'],\n",
       " ['jabongatpumaurbanstampede', 'an', '7', 'timely', 'arrival', ':)'],\n",
       " ['waiter', 'bill', 'sir', 'customer', 'ok', 'kitchen', ':D'],\n",
       " ['title', 'say', ':D'],\n",
       " ['hey', 'almost', 'time', 'visit', 'city', ':)'],\n",
       " ['keep', 'inside', 'pocket', 'ur', 'wripped', 'jean', ':)'],\n",
       " ['beautiful', ':)'],\n",
       " ['well', 'haha', ':D'],\n",
       " ['love',\n",
       "  'connie',\n",
       "  'fabulous',\n",
       "  'ship',\n",
       "  'amazing',\n",
       "  'crew',\n",
       "  'staff',\n",
       "  'great',\n",
       "  'time',\n",
       "  ':-)'],\n",
       " ['hi', 'sweetan', 'best', 'ask', ':)', 'great', 'day', 'fun', 'filming'],\n",
       " ['nope', ':-)'],\n",
       " [\"that's\", 'ok', 'thanks', 'follow', ':)'],\n",
       " ['mum', 'beg', 'watch', 'soprano', \"i'll\", 'watch', ':-)'],\n",
       " ['follow', 'back', 'please', ':)'],\n",
       " ['oh', 'fun', ':)'],\n",
       " [\"that's\", 'great', 'hear', ':D'],\n",
       " ['also', 'ff', 'ukraine', ':)'],\n",
       " ['hi',\n",
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       "  'babe',\n",
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       " ['hi',\n",
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       "  'si',\n",
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       "  'make',\n",
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       "  ':)',\n",
       "  'xx'],\n",
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       "  'feminist',\n",
       "  'fight',\n",
       "  'right',\n",
       "  'act',\n",
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       "  'little',\n",
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       "  ':-)',\n",
       "  'goodnight'],\n",
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       "  'caroline',\n",
       "  'guy',\n",
       "  'say',\n",
       "  'mighty',\n",
       "  'fine',\n",
       "  '🔥',\n",
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       "  'little',\n",
       "  'make',\n",
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       "  'hbd',\n",
       "  '❤',\n",
       "  '️'],\n",
       " ['follback', ':)'],\n",
       " ['time', 'jog', ':p'],\n",
       " ['place', 'hope', ':)', '’', 'pro', 'remote', 'work', 'travel', ';)'],\n",
       " ['newly', 'list', 'ebay', 'store', ':-)', '...'],\n",
       " ['new',\n",
       "  'disneyinfinity',\n",
       "  'starwars',\n",
       "  'character',\n",
       "  'look',\n",
       "  'amazing',\n",
       "  'preorder',\n",
       "  'starter',\n",
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       "  ':D'],\n",
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       "  'tweet',\n",
       "  'hit',\n",
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       "  '...',\n",
       "  'one',\n",
       "  'ever',\n",
       "  'worth',\n",
       "  'try',\n",
       "  ':)'],\n",
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       " ['chant', 'jai', 'italy', '100', 'time', 'fast', ':)'],\n",
       " ['heeeyyy', 'follow', 'fan', 'account', 'thank', ':)'],\n",
       " ['uk', ':)'],\n",
       " ['thank', ':D'],\n",
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       " ['u', 'welcome', ':-)', '♥'],\n",
       " ['good', ':)'],\n",
       " [\"here's\", '★', '★', '★', 'review'],\n",
       " ['hi',\n",
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       "  'let',\n",
       "  'know',\n",
       "  'city',\n",
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       "  'work',\n",
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       " ['get', 'thanks', 'g', ':)'],\n",
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       " ['hug', 'ang', 'kiss', 'philippine', ':)'],\n",
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       " ['yes', 'work', ':)'],\n",
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       "  'great',\n",
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       "  'specialise',\n",
       "  'thermal',\n",
       "  'image',\n",
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       "  '–',\n",
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       "  '😀',\n",
       "  '😁',\n",
       "  '😂',\n",
       "  '😃',\n",
       "  '😄',\n",
       "  '😅',\n",
       "  '😉',\n",
       "  'give',\n",
       "  'dear',\n",
       "  'worry',\n",
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       " ['tombraider', 'hype', 'think', 'might', 'like', ':D'],\n",
       " ['oh', 'oh', 'oh', 'thejuiceinthemix', 'rela', 'building', ':)'],\n",
       " ['low', 'priority', 'match', ':)', 'hahaha'],\n",
       " ['fback', ':)'],\n",
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       "  'harry',\n",
       "  'dm',\n",
       "  'bc',\n",
       "  'wanna',\n",
       "  'give',\n",
       "  'surprise',\n",
       "  'friend',\n",
       "  'birthday',\n",
       "  'wanna',\n",
       "  'make',\n",
       "  'happy',\n",
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       "  'time',\n",
       "  '2',\n",
       "  'collapse',\n",
       "  'chaotic',\n",
       "  'cosas',\n",
       "  '<---',\n",
       "  'note',\n",
       "  'alliteration',\n",
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       " ['best', 'want', 'body', ':)'],\n",
       " ['natgeo',\n",
       "  'new',\n",
       "  'show',\n",
       "  'u',\n",
       "  \"can't\",\n",
       "  'lick',\n",
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       "  'seem',\n",
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       "  '7',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['“', 'emu', 'stoke', 'thank', ':)'],\n",
       " ['wake', 'yo', 'fav', 'tweet', 'make', 'day', ':)', '😂', '😂'],\n",
       " ['remember', 'need', \"people's\", 'approval', \"god's\", 'approval', ':-)'],\n",
       " ['jisung', 'kid', 'sunshine', ':)'],\n",
       " ['mm', 'okay', 'thank', ':)'],\n",
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       "  'u',\n",
       "  'right',\n",
       "  'nicola',\n",
       "  'forward',\n",
       "  ':)',\n",
       "  'brighten',\n",
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       "  ':D',\n",
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       " ['follow'],\n",
       " ['congrats', ':)'],\n",
       " ['hi',\n",
       "  'brian',\n",
       "  \"i'll\",\n",
       "  'get',\n",
       "  'ship',\n",
       "  'today',\n",
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       "  'week',\n",
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       " ['good', 'fun', 'time', 'ol', 'bone', 'creaking', ':)'],\n",
       " ['eh', 'abuti', 'welcome', 'tweetland', '...', 'lol', ':p'],\n",
       " ['thx', 'android', 'support', 'xmas', ':)'],\n",
       " ['great', 'skyblock', 'stream', ':)'],\n",
       " ['im', 'standing', 'always', 'belieber', ':)', 'bcause', '2009', 'die', ':)'],\n",
       " ['stream', 'twitch', 'join', ':D'],\n",
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       " ['would', 'like', ':)', 'xo'],\n",
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       "  'nuka',\n",
       "  'penacova',\n",
       "  'djset',\n",
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       " ['hahaha',\n",
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       "  'anytime',\n",
       "  'wanna',\n",
       "  'taste',\n",
       "  'oh',\n",
       "  'yer',\n",
       "  'address',\n",
       "  'send',\n",
       "  ':)'],\n",
       " ['thanks', 'team', 'yellow', ':)', 'mtn', '8'],\n",
       " ['maganda', 'look', 'pretty', 'short', 'hair', 'cute', ':D'],\n",
       " ['good', 'morning', 'gorgeous', 'mistress', 'saphire', ':)'],\n",
       " [\"i'm\", 'work', \"i'm\", 'busy', 'help', 'finish', 'im', 'home', ':)'],\n",
       " ['thanks',\n",
       "  'amazing',\n",
       "  '4000',\n",
       "  'follower',\n",
       "  'instagram',\n",
       "  '´',\n",
       "  'among',\n",
       "  'yet',\n",
       "  'feel',\n",
       "  'free',\n",
       "  'connect',\n",
       "  ':-)',\n",
       "  '...'],\n",
       " ['coconut', 'sambal', 'mussel', 'recipe', ':-)'],\n",
       " ['thanks', 'kalin', ':)'],\n",
       " ['follow', 'mixcloud', ':)'],\n",
       " ['fback', ':)'],\n",
       " ['thankyou', 'greeting', 'australia', ':)'],\n",
       " ['cant',\n",
       "  'work',\n",
       "  'sarcasm',\n",
       "  ':)',\n",
       "  'know',\n",
       "  'chelsea',\n",
       "  'support',\n",
       "  'think',\n",
       "  'he',\n",
       "  'useless',\n",
       "  'come',\n",
       "  'ok'],\n",
       " ['follow', 'back', ':)'],\n",
       " ['come',\n",
       "  'back',\n",
       "  'next',\n",
       "  'thursday',\n",
       "  'still',\n",
       "  'hang',\n",
       "  ':-)',\n",
       "  'hehe',\n",
       "  'say',\n",
       "  'hi',\n",
       "  'love',\n",
       "  'u'],\n",
       " ['benson',\n",
       "  'gorgeous',\n",
       "  'thank',\n",
       "  'much',\n",
       "  'share',\n",
       "  'u',\n",
       "  ':)',\n",
       "  'also',\n",
       "  'enter',\n",
       "  'facebook',\n",
       "  '...'],\n",
       " ['look', 'solid', '16/17', ':)'],\n",
       " ['great', 'night', ':D'],\n",
       " ['30', '°', 'c', '😜', 'change', 'day', 'good', ':)'],\n",
       " ['add',\n",
       "  'snapchat',\n",
       "  'maryhicks',\n",
       "  '18',\n",
       "  'snapchat',\n",
       "  'kikmeboys',\n",
       "  'photooftheday',\n",
       "  'fuck',\n",
       "  'chat',\n",
       "  'musicbiz',\n",
       "  'sheskindahot',\n",
       "  ':)'],\n",
       " ['fleekile', 'mbalula', 'say', 'repeat', 'love', 'south', 'africa', ':)'],\n",
       " ['friend',\n",
       "  'make',\n",
       "  'fun',\n",
       "  'fact',\n",
       "  'mexican',\n",
       "  'hurt',\n",
       "  'feeling',\n",
       "  'leave',\n",
       "  'scar',\n",
       "  'life',\n",
       "  ':)'],\n",
       " ['office', 'today', ':)'],\n",
       " ['like', 'amazing', 'donut', 'recipe', 'share', 'foiegras', 'lover', ':)'],\n",
       " ['despite', 'weather', 'today', 'wedding', 'go', 'beautiful', ':)'],\n",
       " ['tony', 'stark', ':)', 'incredible', 'tony', 'picture'],\n",
       " ['sit', 'write', 'poem', 'story', \"that's\", 'bubble', 'head', ':)'],\n",
       " ['last', 'night', ':)'],\n",
       " ['dale', 'send', 'billion', 'kiss', ':)', 'magical', 'day'],\n",
       " ['might', 'work', ':)', 'great', 'weekend', 'op'],\n",
       " ['smile', 'friday', ':)', 'tgif', 'weekend'],\n",
       " ['cast', 'vote', 'next', 'election', ':)', 'jcreport'],\n",
       " ['do', 'thank', 'tweet', ':)'],\n",
       " ['oh', 'piggin', 'go', 'yer', 'give', 'u', 'peace', ':)'],\n",
       " ['appreciate', 'follow', ':)', 'hear', 'botanical', 'soap'],\n",
       " ['love', 'u', '2', ':-)'],\n",
       " ['late', 'upload', 'freshly', 'do', '3weeks', 'old', 'heal', ':)'],\n",
       " ['oh', 'bed', 'haha', \"can't\", 'sleep', 'though', 'day', 'exciting', ':)'],\n",
       " ['thx', 'tobi-bro', ':D'],\n",
       " ['good', 'think', 'first', 'isp', ':)'],\n",
       " [\"we'll\", 'steel', 'next', 'wednesday', 'see', 'like', ':)'],\n",
       " ['hey', ':)'],\n",
       " ['definitely',\n",
       "  'love',\n",
       "  'make',\n",
       "  'people',\n",
       "  'smile',\n",
       "  'cause',\n",
       "  'swear',\n",
       "  'since',\n",
       "  'meet',\n",
       "  'earlier',\n",
       "  'stop',\n",
       "  'smile',\n",
       "  ':)',\n",
       "  'love',\n",
       "  'cam',\n",
       "  '😭',\n",
       "  '❤',\n",
       "  '️'],\n",
       " ['...', 'except', 'lord', \"masha'allah\", ':)'],\n",
       " ['french',\n",
       "  'fan',\n",
       "  'make',\n",
       "  'movie',\n",
       "  'wwat',\n",
       "  'france',\n",
       "  'last',\n",
       "  'year',\n",
       "  'video',\n",
       "  'photo',\n",
       "  ':)'],\n",
       " ['fix', 'thanks', 'feedback', ':)'],\n",
       " ['thanks',\n",
       "  'everyone',\n",
       "  'come',\n",
       "  'stream',\n",
       "  ':D',\n",
       "  'hope',\n",
       "  'guys',\n",
       "  'enjoy',\n",
       "  'night'],\n",
       " ['yaaay', 'thx', ':)'],\n",
       " ['look', 'forward', 'review', ':-)'],\n",
       " ['thank', 'beiruting', ':)'],\n",
       " ['fback', ':)'],\n",
       " ['thanks', 'update', 'profile', 'page', ':-)'],\n",
       " ['lovely', 'coffee', ':)'],\n",
       " [\"here's\", 'cute', 'panda', 'make', 'day', ':)'],\n",
       " ['thank', 'eonnie', ':)'],\n",
       " ['hi', 'saw', 'u', 'follow', 'think', 'u', 'might', 'like', 'dark'],\n",
       " ['favourite', ':)', 'cream', 'soda', ':)'],\n",
       " ['love',\n",
       "  'body',\n",
       "  'fuller',\n",
       "  'shit',\n",
       "  'even',\n",
       "  'lol',\n",
       "  \"i'm\",\n",
       "  'happy',\n",
       "  'healthy',\n",
       "  ':)',\n",
       "  'happy',\n",
       "  'happy',\n",
       "  '..',\n",
       "  '💓'],\n",
       " ['rettweet', ':-)'],\n",
       " ['real',\n",
       "  'mvg',\n",
       "  'valuable',\n",
       "  'girlfriend',\n",
       "  'stay',\n",
       "  'till',\n",
       "  'madrid',\n",
       "  'game',\n",
       "  'start',\n",
       "  ':-)'],\n",
       " ['sore', 'ya', ':)'],\n",
       " [\"i'm\", 'excited', 'definitely', 'meet', ':)'],\n",
       " ['come',\n",
       "  'bergerac',\n",
       "  'first',\n",
       "  'team',\n",
       "  'leave',\n",
       "  'u21',\n",
       "  \"i'd\",\n",
       "  'know',\n",
       "  'check',\n",
       "  'chant',\n",
       "  ':-)'],\n",
       " [':)', 'choice', 'food', 'leave', 'individual'],\n",
       " ['episode',\n",
       "  'excellent',\n",
       "  'far',\n",
       "  ':-)',\n",
       "  'love',\n",
       "  'adam',\n",
       "  \"beach's\",\n",
       "  'movie',\n",
       "  'show',\n",
       "  \"i'm\",\n",
       "  'look',\n",
       "  'forward',\n",
       "  'see',\n",
       "  'suicide',\n",
       "  'squad',\n",
       "  'next',\n",
       "  'year'],\n",
       " ['grow',\n",
       "  'fond',\n",
       "  'christopher',\n",
       "  'like',\n",
       "  'initially',\n",
       "  'cocky',\n",
       "  'really',\n",
       "  'prove',\n",
       "  \"attitude's\",\n",
       "  'improve',\n",
       "  ':D'],\n",
       " ['sound',\n",
       "  'good',\n",
       "  'dm',\n",
       "  'email',\n",
       "  'address',\n",
       "  'suggest',\n",
       "  'date',\n",
       "  'coffee',\n",
       "  ':)'],\n",
       " ['indeed', 'many', 'thanks', ':-)'],\n",
       " ['smile', 'even', 'pain', ':)'],\n",
       " ['hi', 'happys', ':)'],\n",
       " ['funny', 'intelligent', 'strong', 'funny', 'funny', '...', ':-)'],\n",
       " ['hello', ':)', 'get', 'youth', 'job', 'opportunity', 'follow'],\n",
       " ['use', 'cs', ':)'],\n",
       " ['ever', 'watch', 'certain', \"people's\", 'snapchat', 'bc', 'know', ':-)'],\n",
       " [\"that's\", 'ok', 'know', 'busy', ':)'],\n",
       " ['last', '2', 'exam', ':)'],\n",
       " ['forgot', 'u', ':)'],\n",
       " ['fun', 'fact', 'love', 'meet', 'new', 'people', ':)'],\n",
       " ['know',\n",
       "  'home-based',\n",
       "  'office',\n",
       "  'busy',\n",
       "  'feel',\n",
       "  ':-)',\n",
       "  'pity',\n",
       "  'knee',\n",
       "  'happen'],\n",
       " ['sale',\n",
       "  'fleur',\n",
       "  'dress',\n",
       "  'cream',\n",
       "  'readystock_hijabmart',\n",
       "  'idr',\n",
       "  '325.000',\n",
       "  'idr',\n",
       "  '200.000',\n",
       "  ':)'],\n",
       " ['thankyou', ':)'],\n",
       " ['follow'],\n",
       " ['tompolo',\n",
       "  'meeting',\n",
       "  'aim',\n",
       "  'stop',\n",
       "  'sale',\n",
       "  'oil',\n",
       "  'cannot',\n",
       "  'find',\n",
       "  'buyer',\n",
       "  ':D'],\n",
       " [\"that's\", 'true', 'disappoint', 'look', 'forward', 'paper', 'town', ':)'],\n",
       " [\"that's\", 'need', 'know', 'everything', 'go', 'okay', ':-)'],\n",
       " ['say', 'less', 'slacking', 'get', 'crack', ':)'],\n",
       " ['know', 'name', 'particularly', 'striking', 'happy', 'day', ':)'],\n",
       " ['hey', \"here's\", 'invite', 'join', 'scope', 'influencer', ':)'],\n",
       " ['31', 'bad', 'mam', ':p'],\n",
       " ['lovely', 'look', 'cake', 'bet', 'taste', 'good', ':-)'],\n",
       " ['feytyaz', 'follback', 'ya', ':)'],\n",
       " ['find',\n",
       "  'last',\n",
       "  'night',\n",
       "  'let',\n",
       "  'say',\n",
       "  'instant',\n",
       "  'stiffening',\n",
       "  'interest',\n",
       "  ':)'],\n",
       " ['rettweet', ':-)'],\n",
       " ['fback', ':)'],\n",
       " ['rettweet', ':-)'],\n",
       " ['ricky_febs', 'follback', 'ya', ':)'],\n",
       " ['get',\n",
       "  'secret',\n",
       "  'grindea',\n",
       "  'courier',\n",
       "  'crypt',\n",
       "  'possibly',\n",
       "  'arma',\n",
       "  '3',\n",
       "  'record',\n",
       "  'today',\n",
       "  '...',\n",
       "  'gosh',\n",
       "  'new',\n",
       "  'game',\n",
       "  'look',\n",
       "  'like',\n",
       "  'limbo',\n",
       "  ':)'],\n",
       " ['follow'],\n",
       " ['thanks', 'retweeting', 'orchard', 'art', 'show', 'super', 'weekend', ':)'],\n",
       " ['karachi',\n",
       "  'ka',\n",
       "  'venice',\n",
       "  'rain',\n",
       "  ':)',\n",
       "  '“',\n",
       "  'several',\n",
       "  'part',\n",
       "  'karachi',\n",
       "  'witness',\n",
       "  'accumulate',\n",
       "  'rain',\n",
       "  'water'],\n",
       " ['maroon', 'cocktail', 'dress'],\n",
       " ['fback', 'po', ':)'],\n",
       " ['0-100', 'real', 'quick', ':)'],\n",
       " ['morning',\n",
       "  'mine',\n",
       "  '1100d',\n",
       "  'usually',\n",
       "  'auto-focus',\n",
       "  'use',\n",
       "  'manual',\n",
       "  'really',\n",
       "  'close',\n",
       "  'like',\n",
       "  'shoot',\n",
       "  'vein',\n",
       "  'crackle',\n",
       "  'glaze',\n",
       "  ':)'],\n",
       " ['new', 'layout', 'look', 'bomb', ':-)', 'g'],\n",
       " ['thanks',\n",
       "  'connect',\n",
       "  'hope',\n",
       "  'great',\n",
       "  'day',\n",
       "  'social',\n",
       "  'website',\n",
       "  'question',\n",
       "  'ask',\n",
       "  ':-)'],\n",
       " ['pake', ':)'],\n",
       " ['hi', 'make', 'change', 'design', 'hope', 'like', ':)'],\n",
       " ['joim', 'fee', 'troop', ':)'],\n",
       " ['brand',\n",
       "  'want',\n",
       "  'review',\n",
       "  'beauty',\n",
       "  'product',\n",
       "  'blog',\n",
       "  'mail',\n",
       "  'ladolcevitainluxembourg@hotmail.com',\n",
       "  'prrequest',\n",
       "  'journorequest',\n",
       "  ':)'],\n",
       " ['the_madstork', 'follback', 'ya', ':)'],\n",
       " ['good', 'luck', 'shaun', ':)'],\n",
       " ['yes', ':)'],\n",
       " ['anyone', 'want', 'add', 'bot', 'dm', ':)', 'bot'],\n",
       " ['chloe',\n",
       "  'watch',\n",
       "  'let',\n",
       "  'yesterday',\n",
       "  'really',\n",
       "  'awesome',\n",
       "  'really',\n",
       "  'talented',\n",
       "  'intelligent',\n",
       "  'actress',\n",
       "  'beautiful',\n",
       "  ':)'],\n",
       " ['could', 'get', 'free', 'solo', 'dm', 'give', 'away', ':)', 'xoxo'],\n",
       " ['thanks', 'share', 'wish', 'wicked', 'weekend', ':)'],\n",
       " ['hola',\n",
       "  'juan',\n",
       "  '..',\n",
       "  'sending',\n",
       "  'big',\n",
       "  'hi',\n",
       "  'houston',\n",
       "  'tx',\n",
       "  ':)',\n",
       "  \"i've\",\n",
       "  'fan',\n",
       "  'jenni',\n",
       "  'family',\n",
       "  \"year's\",\n",
       "  'stumble',\n",
       "  'upon',\n",
       "  'video'],\n",
       " ['prob.nice', 'choker', 'btw', ':)'],\n",
       " ['seouljins', ':)', 'fine', 'tbh'],\n",
       " ['photoset',\n",
       "  'sadomasochistsparadise',\n",
       "  'wynter',\n",
       "  'bottom',\n",
       "  'outtake',\n",
       "  ':)',\n",
       "  'sadomasochist',\n",
       "  '’',\n",
       "  'paradise',\n",
       "  'cuties'],\n",
       " ['make', 'day', 'smile', ':)'],\n",
       " ['fback', ':)'],\n",
       " [':D', 'ty', 'bby'],\n",
       " ['please', 'enjoy', 'clip', 'lose', 'shit', 'cypher', ':)'],\n",
       " ['next', 'week', 'office', 'let', 'go', ':)'],\n",
       " ['thank', 'follow', ':D'],\n",
       " ['stats',\n",
       "  'day',\n",
       "  'arrive',\n",
       "  '2',\n",
       "  'new',\n",
       "  'follower',\n",
       "  'unfollowers',\n",
       "  ':)',\n",
       "  'via'],\n",
       " ['amen', 'thanks', ':)'],\n",
       " ['hi',\n",
       "  'bam',\n",
       "  'follow',\n",
       "  'bestfriend',\n",
       "  'love',\n",
       "  'lot',\n",
       "  ':)',\n",
       "  'see',\n",
       "  'warsaw',\n",
       "  '<3',\n",
       "  'love',\n",
       "  '<3',\n",
       "  'x32'],\n",
       " ['follow'],\n",
       " ['paper', 'girl', ':D'],\n",
       " ['know', 'would', 'lovely', 'pic', ':)', 'x'],\n",
       " ['plant', 'people', 'allow', 'thing', 'every', 'thing', ':p'],\n",
       " ['corner', 'fucking', 'dope', 'get', 'addict', '..', 'great', 'job', ':D'],\n",
       " ['bby', 'gurl', ':)'],\n",
       " ['hey', 'hey', ':D'],\n",
       " ['still', 'suck', 'edit', 'turn', 'something', 'special', 'owe', 'guy', ':)'],\n",
       " ['visit', 'blog'],\n",
       " ['ugly', 'daniel', 'good', 'ape', ':)'],\n",
       " ['happy', 'bday', 'saar', '...', 'great', 'year', 'ahead', '...', ':)'],\n",
       " ['think',\n",
       "  'might',\n",
       "  'saw',\n",
       "  'love',\n",
       "  'verse',\n",
       "  'butterfly',\n",
       "  'part',\n",
       "  'bonus',\n",
       "  ':)'],\n",
       " ['thank', ':-)', 'ok', 'fun', 'enjoy', 'day', 'u'],\n",
       " ['well', 'good', 'morning', ':D'],\n",
       " ['would', 'follow', ':)'],\n",
       " ['busy',\n",
       "  'productive',\n",
       "  'day',\n",
       "  'fill',\n",
       "  'tear',\n",
       "  'hour',\n",
       "  'hour',\n",
       "  'laughter',\n",
       "  'today',\n",
       "  'good',\n",
       "  'day',\n",
       "  ':)'],\n",
       " ['hi', '5sos', 'ticket', 'dm', ':)'],\n",
       " ['yummmyyy', '...', ':-)', '—', 'eat', 'dosa'],\n",
       " [':D'],\n",
       " ['probably',\n",
       "  'easy',\n",
       "  'meet',\n",
       "  'station',\n",
       "  'unless',\n",
       "  'particularly',\n",
       "  'want',\n",
       "  'show',\n",
       "  'house',\n",
       "  ':)'],\n",
       " ['huge', 'warm', 'welcome', ':-)'],\n",
       " ['achi',\n",
       "  'im',\n",
       "  'busy',\n",
       "  'next',\n",
       "  'week',\n",
       "  'exam',\n",
       "  'hope',\n",
       "  'understand',\n",
       "  'cant',\n",
       "  'tweet',\n",
       "  'youuu',\n",
       "  'bawi',\n",
       "  'ako',\n",
       "  'queenesther',\n",
       "  ':)'],\n",
       " ['look', 'sharp', ':-)'],\n",
       " ['yes',\n",
       "  'im',\n",
       "  '1',\n",
       "  'year',\n",
       "  'young',\n",
       "  'u',\n",
       "  ':-)',\n",
       "  'wonder',\n",
       "  'youre',\n",
       "  'huge',\n",
       "  'boy'],\n",
       " [\"i'm\", 'play', 'brain', 'dot', 'braindots'],\n",
       " ['ha', 'one', 'picture', ':-)'],\n",
       " ['ready', ':)', 'poldi', 'cimbom'],\n",
       " ['thanks', 'share', ':)'],\n",
       " ['fback', ':)'],\n",
       " ['follow'],\n",
       " ['happy', 'birthday', 'buddy', ':D'],\n",
       " ['thank', ':-)'],\n",
       " ['sigh', 'bruhhh', '“', 'call', 'daddy', 'one', 'time', ':)', '”'],\n",
       " ...]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_x"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cfbce29",
   "metadata": {},
   "source": [
    "Expected output:\n",
    "\n",
    "The length of the longest tweet is 51 tokens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a20bd3ee",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your max_len function\n",
    "w1_unittest.test_max_length(max_length)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34e550c2",
   "metadata": {},
   "source": [
    "<a name=\"ex-3\"></a>\n",
    "### Exercise 3 - padded_sequence\n",
    "Implement `padded_sequence` function to transform sequences of words into padded sequences of numbers. A couple of things to notice:\n",
    "\n",
    "- The term `tensor` is used to refer to the encoded tweet but the function should return a regular python list, not a `tf.tensor`\n",
    "- There is no need to truncate the tweet if it exceeds `max_len` as you already know the maximum length of the tweets beforehand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fe6597fa",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: padded_sequence\n",
    "def padded_sequence(tweet, vocab_dict, max_len, unk_token='[UNK]'):\n",
    "    \"\"\"transform sequences of words into padded sequences of numbers\n",
    "\n",
    "    Args:\n",
    "        tweet (list): A single tweet encoded as a list of strings.\n",
    "        vocab_dict (dict): Vocabulary.\n",
    "        max_len (int): Length of the longest tweet.\n",
    "        unk_token (str, optional): Unknown token. Defaults to '[UNK]'.\n",
    "\n",
    "    Returns:\n",
    "        list: Padded tweet encoded as a list of int.\n",
    "    \"\"\"\n",
    "    ### START CODE HERE ###\n",
    "    \n",
    "    # Find the ID of the UNK token, to use it when you encounter a new word\n",
    "    unk_ID = vocab_dict.get(unk_token, 0)  # Default to 0 if unk_token is not in vocab_dict\n",
    "    \n",
    "    # First convert the words to integers by looking up the vocab_dict\n",
    "    tweet_ids = [vocab_dict.get(word, unk_ID) for word in tweet]\n",
    "    \n",
    "    # Then pad the tensor with zeroes up to the length max_len\n",
    "    padded_tensor = tweet_ids[:max_len] + [0] * (max_len - len(tweet_ids))\n",
    "\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    return padded_tensor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3752b8dc",
   "metadata": {},
   "source": [
    "Test the function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "f8766862",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your padded_sequence function\n",
    "w1_unittest.test_padded_sequence(padded_sequence)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4dfd15c",
   "metadata": {},
   "source": [
    "Pad the train and validation dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "38f7fcbd",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "train_x_padded = [padded_sequence(x, vocab, max_len) for x in train_x]\n",
    "val_x_padded = [padded_sequence(x, vocab, max_len) for x in val_x]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fde3269",
   "metadata": {},
   "source": [
    "<a name=\"3\"></a>\n",
    "## 3 - Define the structure of the neural network layers\n",
    "\n",
    "In this part, you will write your own functions and layers for the neural network to test your understanding of the implementation. It will be similar to the one used in Keras and PyTorch. Writing your own small framework will help you understand how they all work and use them effectively in the future.\n",
    "\n",
    "You will implement the ReLU and sigmoid functions, which you will use as activation functions for the neural network, as well as a fully connected (dense) layer."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4809299",
   "metadata": {},
   "source": [
    "<a name=\"3-1\"></a>\n",
    "### 3.1 - ReLU\n",
    "You will now implement the ReLU activation in a function below. The ReLU function looks as follows: \n",
    "<img src = \"images/relu.jpg\" style=\"width:300px;height:150px;\"/>\n",
    "\n",
    "$$ \\mathrm{ReLU}(x) = \\mathrm{max}(0,x) $$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca253367",
   "metadata": {},
   "source": [
    "<a name=\"ex-4\"></a>\n",
    "### Exercise 4 - relu\n",
    "**Instructions:** Implement the ReLU activation function below. Your function should take in a matrix or vector and it should transform all the negative numbers into 0 while keeping all the positive numbers intact. \n",
    "\n",
    "Notice you can get the maximum of two numbers by using [np.maximum](https://numpy.org/doc/stable/reference/generated/numpy.maximum.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f1c365d1",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: relu\n",
    "def relu(x):\n",
    "    '''Relu activation function implementation\n",
    "    Input: \n",
    "        - x (numpy array)\n",
    "    Output:\n",
    "        - activation (numpy array): input with negative values set to zero\n",
    "    '''\n",
    "    ### START CODE HERE ###\n",
    "\n",
    "    activation = np.maximum(0, x)\n",
    "\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    return activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6027ee6e",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test data is:\n",
      "[[-2. -1.  0.]\n",
      " [ 0.  1.  2.]]\n",
      "\n",
      "Output of relu is:\n",
      "[[0. 0. 0.]\n",
      " [0. 1. 2.]]\n"
     ]
    }
   ],
   "source": [
    "# Check the output of your function\n",
    "x = np.array([[-2.0, -1.0, 0.0], [0.0, 1.0, 2.0]], dtype=float)\n",
    "print(\"Test data is:\")\n",
    "print(x)\n",
    "print(\"\\nOutput of relu is:\")\n",
    "print(relu(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6cb21e3",
   "metadata": {},
   "source": [
    "**Expected Output:**\n",
    "```\n",
    "Test data is:\n",
    "[[-2. -1.  0.]\n",
    " [ 0.  1.  2.]]\n",
    " \n",
    "Output of relu is:\n",
    "[[0. 0. 0.]\n",
    " [0. 1. 2.]]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "09460d00",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your relu function\n",
    "w1_unittest.test_relu(relu)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bad16e4",
   "metadata": {},
   "source": [
    "<a name=\"3-2\"></a>\n",
    "### 3.2 - Sigmoid\n",
    "You will now implement the sigmoid activation in a function below. The sigmoid function looks as follows: \n",
    "<img src = \"images/sigmoid.jpg\" style=\"width:300px;height:150px;\"/>\n",
    "\n",
    "$$ \\mathrm{sigmoid}(x) = \\frac{1}{1 + e^{-x}} $$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa5bbd47",
   "metadata": {},
   "source": [
    "<a name=\"ex-5\"></a>\n",
    "### Exercise 5 - sigmoid\n",
    "**Instructions:** Implement the sigmoid activation function below. Your function should take in a matrix or vector and it should transform all the numbers according to the formula above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "1d5d3268",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: sigmoid\n",
    "def sigmoid(x):\n",
    "    '''Sigmoid activation function implementation\n",
    "    Input: \n",
    "        - x (numpy array)\n",
    "    Output:\n",
    "        - activation (numpy array)\n",
    "    '''\n",
    "    ### START CODE HERE ###\n",
    "\n",
    "    activation = 1 / (1 + np.exp(-x))\n",
    "\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    return activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "31275d11",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test data is:\n",
      "[[-1000.    -1.     0.]\n",
      " [    0.     1.  1000.]]\n",
      "\n",
      "Output of sigmoid is:\n",
      "[[0.         0.26894142 0.5       ]\n",
      " [0.5        0.73105858 1.        ]]\n"
     ]
    }
   ],
   "source": [
    "# Check the output of your function\n",
    "x = np.array([[-1000.0, -1.0, 0.0], [0.0, 1.0, 1000.0]], dtype=float)\n",
    "print(\"Test data is:\")\n",
    "print(x)\n",
    "print(\"\\nOutput of sigmoid is:\")\n",
    "print(sigmoid(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3df79772",
   "metadata": {},
   "source": [
    "**Expected Output:**\n",
    "```\n",
    "Test data is:\n",
    "[[-1000.    -1.     0.]\n",
    " [    0.     1.  1000.]]\n",
    "\n",
    "Output of sigmoid is:\n",
    "[[0.         0.26894142 0.5       ]\n",
    " [0.5        0.73105858 1.        ]]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "87150bd2",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your sigmoid function\n",
    "w1_unittest.test_sigmoid(sigmoid)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfd2861b",
   "metadata": {},
   "source": [
    "<a name=\"3.3\"></a>\n",
    "### 3.3 - Dense Class \n",
    "\n",
    "Implement the weight initialization in the `__init__` method.\n",
    "- Weights are initialized with a random key.\n",
    "- The shape of the weights (num_rows, num_cols) should equal the number of columns in the input data (this is in the last column) and the number of units respectively.\n",
    "    - The number of rows in the weight matrix should equal the number of columns in the input data `x`.  Since `x` may have 2 dimensions if it represents a single training example (row, col), or three dimensions (batch_size, row, col), get the last dimension from the tuple that holds the dimensions of x.\n",
    "    - The number of columns in the weight matrix is the number of units chosen for that dense layer.\n",
    "- The values generated should have a mean of 0 and standard deviation of `stdev`.\n",
    "    - To initialize random weights, a random generator is created using `random_generator = np.random.default_rng(seed=random_seed)`. This part is implemented for you. You will use `random_generator.normal(...)` to create your random weights. Check [here](https://numpy.org/doc/stable/reference/random/generator.html) how the random generator works.\n",
    "    - Please don't change the `random_seed`, so that the results are reproducible for testing (and you can be fairly graded).\n",
    "\n",
    "Implement the `forward` function of the Dense class. \n",
    "- The forward function multiplies the input to the layer (`x`) by the weight matrix (`W`)\n",
    "\n",
    "$$\\mathrm{forward}(\\mathbf{x},\\mathbf{W}) = \\mathbf{xW} $$\n",
    "\n",
    "- You can use `numpy.dot` to perform the matrix multiplication."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2917e87b",
   "metadata": {},
   "source": [
    "<a name=\"ex-6\"></a>\n",
    "### Exercise 6 - Dense\n",
    "\n",
    "Implement the `Dense` class. You might want to check how normal random numbers can be generated with numpy by checking the [docs](https://numpy.org/doc/stable/reference/random/generated/numpy.random.Generator.normal.html#numpy.random.Generator.normal)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4ede0912",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# GRADED CLASS: Dense\n",
    "import numpy as np\n",
    "\n",
    "class Dense:\n",
    "    \"\"\"\n",
    "    A dense (fully-connected) layer.\n",
    "\n",
    "    Attributes:\n",
    "        n_units (int): The number of units in this layer.\n",
    "        random_generator (np.random.default_rng): Random number generator for weight initialization.\n",
    "        activation (str or callable): Activation function to be applied.\n",
    "        weights (np.ndarray): Weight matrix of the layer.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, n_units, input_shape, activation, stdev=0.1, random_seed=42):\n",
    "        \"\"\"\n",
    "        Initializes the Dense layer.\n",
    "\n",
    "        Args:\n",
    "            n_units (int): The number of units in this layer.\n",
    "            input_shape (tuple): Shape of the input data.\n",
    "            activation (str or callable): Activation function to be applied.\n",
    "                String names can be used for common activations (e.g., 'relu', 'sigmoid').\n",
    "            stdev (float, optional): Standard deviation for weight initialization. Defaults to 0.1.\n",
    "            random_seed (int, optional): Random seed for weight initialization. Defaults to 42.\n",
    "        \"\"\"\n",
    "\n",
    "        self.n_units = n_units\n",
    "        self.random_generator = np.random.default_rng(seed=random_seed)\n",
    "        self.activation = activation\n",
    "\n",
    "        # Calculate the weight matrix size based on input shape and number of units\n",
    "        self.weights = self.random_generator.normal(scale=stdev, size=(input_shape[-1], n_units))  # Corrected size calculation\n",
    "\n",
    "    def __call__(self, x):\n",
    "        \"\"\"\n",
    "        Performs the forward pass through the layer.\n",
    "\n",
    "        Args:\n",
    "            x (np.ndarray): Input data.\n",
    "\n",
    "        Returns:\n",
    "            np.ndarray: Output of the layer after applying activation.\n",
    "        \"\"\"\n",
    "        return self.forward(x)\n",
    "\n",
    "    def forward(self, x):\n",
    "        \"\"\"\n",
    "        Performs the forward pass through the layer.\n",
    "\n",
    "        Args:\n",
    "            x (np.ndarray): Input data.\n",
    "\n",
    "        Returns:\n",
    "            np.ndarray: Output of the layer after applying activation.\n",
    "        \"\"\"\n",
    "\n",
    "        # Matrix multiplication between input and weights\n",
    "        dense = np.dot(x, self.weights)\n",
    "\n",
    "        # Apply the activation function\n",
    "        if self.activation is not None:\n",
    "            if isinstance(self.activation, str):\n",
    "                # Handle common activation function names (e.g., 'relu', 'sigmoid')\n",
    "                activation_func = getattr(self, self.activation)\n",
    "                dense = activation_func(dense)\n",
    "            else:\n",
    "                # Call the provided activation function (assumed to be callable)\n",
    "                dense = self.activation(dense)\n",
    "\n",
    "        return dense\n",
    "\n",
    "    # Define common activation functions here (optional)\n",
    "    def relu(self, x):\n",
    "        return np.maximum(0, x)\n",
    "\n",
    "    def sigmoid(self, x):\n",
    "        return 1 / (1 + np.exp(-x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5bc10c8b",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weights are:\n",
      " [[ 0.03047171 -0.10399841  0.07504512  0.09405647 -0.19510352 -0.13021795\n",
      "   0.01278404 -0.03162426 -0.00168012 -0.08530439]\n",
      " [ 0.0879398   0.07777919  0.00660307  0.11272412  0.04675093 -0.08592925\n",
      "   0.03687508 -0.09588826  0.08784503 -0.00499259]\n",
      " [-0.01848624 -0.06809295  0.12225413 -0.01545295 -0.04283278 -0.03521336\n",
      "   0.05323092  0.03654441  0.04127326  0.0430821 ]]\n",
      "Foward function output is: [[0.21436609 0.         3.25266507 0.59085808 0.         0.\n",
      "  1.61446659 0.17914382 1.64338651 0.87149558]]\n"
     ]
    }
   ],
   "source": [
    "# random_key = np.random.get_prng()  # sets random seed\n",
    "z = np.array([[2.0, 7.0, 25.0]]) # input array\n",
    "\n",
    "# Testing your Dense layer \n",
    "dense_layer = Dense(n_units=10, input_shape=z.shape, activation=relu)  #sets  number of units in dense layer\n",
    "\n",
    "print(\"Weights are:\\n\",dense_layer.weights) #Returns randomly generated weights\n",
    "print(\"Foward function output is:\", dense_layer(z)) # Returns multiplied values of units and weights"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56055e63",
   "metadata": {},
   "source": [
    "**Expected Output:**\n",
    "```\n",
    "Weights are:\n",
    " [[ 0.03047171 -0.10399841  0.07504512  0.09405647 -0.19510352 -0.13021795\n",
    "   0.01278404 -0.03162426 -0.00168012 -0.08530439]\n",
    " [ 0.0879398   0.07777919  0.00660307  0.11272412  0.04675093 -0.08592925\n",
    "   0.03687508 -0.09588826  0.08784503 -0.00499259]\n",
    " [-0.01848624 -0.06809295  0.12225413 -0.01545295 -0.04283278 -0.03521336\n",
    "   0.05323092  0.03654441  0.04127326  0.0430821 ]]\n",
    "\n",
    "Foward function output is: [[0.21436609 0.         3.25266507 0.59085808 0.         0.\n",
    "  1.61446659 0.17914382 1.64338651 0.87149558]]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88912018",
   "metadata": {},
   "source": [
    "Test the Dense class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "da1120d5",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your Dense class\n",
    "w1_unittest.test_Dense(Dense)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c2d927a",
   "metadata": {},
   "source": [
    "<a name=\"3-4\"></a>\n",
    "### 3.4 - Model\n",
    "\n",
    "Now you will implement a classifier using neural networks. Here is the model architecture you will be implementing. \n",
    "\n",
    "<img src = \"images/nn.jpg\"/>\n",
    "\n",
    "For the model implementation, you will use `TensorFlow` module, imported as `tf`. Your model will consist of layers and activation functions that you implemented above, but you will take them directly from the tensorflow library.\n",
    "\n",
    "You will use the [tf.keras.Sequential](https://www.tensorflow.org/api_docs/python/tf/keras/Sequential) module, which allows you to stack the layers in a sequence as you want them in the model. You will use the following layers:\n",
    "- [tf.keras.layers.Embedding](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Embedding)\n",
    "    - Turns positive integers (word indices) into vectors of fixed size. You can imagine it as creating one-hot vectors out of indices and then running them through a fully-connected (dense) layer.\n",
    "- [tf.keras.layers.GlobalAveragePooling1D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/GlobalAveragePooling1D)\n",
    "- [tf.keras.layers.Dense](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense)\n",
    "    - Regular fully connected layer\n",
    "    \n",
    "Please use the `help` function to view documentation for each layer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "8a5de20b",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# View documentation on how to implement the layers in tf.\n",
    "# help(tf.keras.Sequential)\n",
    "# help(tf.keras.layers.Embedding)\n",
    "# help(tf.keras.layers.GlobalAveragePooling1D)\n",
    "# help(tf.keras.layers.Dense)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a184816",
   "metadata": {},
   "source": [
    "<a name=\"ex-7\"></a>\n",
    "### Exercise 7 - create_model\n",
    "Implement the create_model function. \n",
    "\n",
    "First you need to create the model. The `tf.keras.Sequential` has been implemented for you. Within it you should put the following layers:\n",
    "- `tf.keras.layers.Embedding` with the size `num_words` times `embeding_dim` and the `input_length` set to the length of the input sequences (which is the length of the longest tweet).\n",
    "- `tf.keras.layers.GlobalAveragePooling1D` with no extra parameters.\n",
    "- `tf.keras.layers.Dense` with the size of one (this is your classification output) and `'sigmoid'` activation passed to the  `activation` keyword parameter.\n",
    "Make sure to separate the layers with a comma.\n",
    "\n",
    "Then you need to compile the model. Here you can look at all the parameters you can set when compiling the model:  [tf.keras.Model](https://www.tensorflow.org/api_docs/python/tf/keras/Model). In this notebook, you just need to set the loss to `'binary_crossentropy'` (because you are doing binary classification with a sigmoid function at the output), the optimizer to `'adam'` and the metrics to `'accuracy'` (so that you can track the accuracy on the training and validation sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1f8deb0d",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "# GRADED FUNCTION: create_model\n",
    "def create_model(num_words, embedding_dim, max_len):\n",
    "    \"\"\"\n",
    "    Creates a text classifier model\n",
    "    \n",
    "    Args:\n",
    "        num_words (int): size of the vocabulary for the Embedding layer input\n",
    "        embedding_dim (int): dimensionality of the Embedding layer output\n",
    "        max_len (int): length of the input sequences\n",
    "    \n",
    "    Returns:\n",
    "        model (tf.keras Model): the text classifier model\n",
    "    \"\"\"\n",
    "    \n",
    "    tf.random.set_seed(123)\n",
    "    \n",
    "    ### START CODE HERE\n",
    "    \n",
    "    model = tf.keras.Sequential([ \n",
    "        tf.keras.layers.Embedding(input_dim=num_words, output_dim=embedding_dim, input_length=max_len),\n",
    "        tf.keras.layers.GlobalAveragePooling1D(),\n",
    "        tf.keras.layers.Dense(1, activation='sigmoid')\n",
    "    ]) \n",
    "    \n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=['accuracy'])\n",
    "\n",
    "    ### END CODE HERE\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9a88700c",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The model is created!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Create the model\n",
    "model = create_model(num_words=num_words, embedding_dim=16, max_len=max_len)\n",
    "\n",
    "print('The model is created!\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "1a0d3f48",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m All tests passed\n"
     ]
    }
   ],
   "source": [
    "# Test your create_model function\n",
    "w1_unittest.test_model(create_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa3495bc",
   "metadata": {},
   "source": [
    "Now you need to prepare the data to put into the model. You already created lists of x and y values and all you need to do now is convert them to `NumPy` arrays, as this is the format that the model is expecting.\n",
    "\n",
    "Then you can create a model with the function you defined above and train it. The trained model should give you about 99.6 % accuracy on the validation set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "5cc20ab8",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data is prepared for training!\n",
      "\n",
      "Training:\n",
      "Epoch 1/20\n",
      "250/250 [==============================] - 16s 52ms/step - loss: 0.6833 - accuracy: 0.6683 - val_loss: 0.6681 - val_accuracy: 0.9880\n",
      "Epoch 2/20\n",
      "250/250 [==============================] - 3s 13ms/step - loss: 0.6352 - accuracy: 0.9475 - val_loss: 0.6018 - val_accuracy: 0.9750\n",
      "Epoch 3/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.5460 - accuracy: 0.9875 - val_loss: 0.5053 - val_accuracy: 0.9910\n",
      "Epoch 4/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.4401 - accuracy: 0.9896 - val_loss: 0.4044 - val_accuracy: 0.9940\n",
      "Epoch 5/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.3421 - accuracy: 0.9941 - val_loss: 0.3170 - val_accuracy: 0.9920\n",
      "Epoch 6/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.2624 - accuracy: 0.9942 - val_loss: 0.2482 - val_accuracy: 0.9960\n",
      "Epoch 7/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.2016 - accuracy: 0.9956 - val_loss: 0.1946 - val_accuracy: 0.9945\n",
      "Epoch 8/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.1563 - accuracy: 0.9962 - val_loss: 0.1547 - val_accuracy: 0.9945\n",
      "Epoch 9/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.1230 - accuracy: 0.9964 - val_loss: 0.1247 - val_accuracy: 0.9955\n",
      "Epoch 10/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.0981 - accuracy: 0.9970 - val_loss: 0.1015 - val_accuracy: 0.9950\n",
      "Epoch 11/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.0794 - accuracy: 0.9969 - val_loss: 0.0840 - val_accuracy: 0.9955\n",
      "Epoch 12/20\n",
      "250/250 [==============================] - 1s 2ms/step - loss: 0.0650 - accuracy: 0.9971 - val_loss: 0.0701 - val_accuracy: 0.9955\n",
      "Epoch 13/20\n",
      "250/250 [==============================] - 1s 2ms/step - loss: 0.0540 - accuracy: 0.9975 - val_loss: 0.0593 - val_accuracy: 0.9960\n",
      "Epoch 14/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.0453 - accuracy: 0.9977 - val_loss: 0.0507 - val_accuracy: 0.9960\n",
      "Epoch 15/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.0385 - accuracy: 0.9979 - val_loss: 0.0437 - val_accuracy: 0.9960\n",
      "Epoch 16/20\n",
      "250/250 [==============================] - 1s 4ms/step - loss: 0.0329 - accuracy: 0.9980 - val_loss: 0.0380 - val_accuracy: 0.9960\n",
      "Epoch 17/20\n",
      "250/250 [==============================] - 1s 2ms/step - loss: 0.0284 - accuracy: 0.9980 - val_loss: 0.0332 - val_accuracy: 0.9960\n",
      "Epoch 18/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.0247 - accuracy: 0.9981 - val_loss: 0.0294 - val_accuracy: 0.9960\n",
      "Epoch 19/20\n",
      "250/250 [==============================] - 1s 3ms/step - loss: 0.0217 - accuracy: 0.9984 - val_loss: 0.0263 - val_accuracy: 0.9960\n",
      "Epoch 20/20\n",
      "250/250 [==============================] - 1s 2ms/step - loss: 0.0191 - accuracy: 0.9983 - val_loss: 0.0236 - val_accuracy: 0.9960\n"
     ]
    }
   ],
   "source": [
    "# Prepare the data\n",
    "train_x_prepared = np.array(train_x_padded)\n",
    "val_x_prepared = np.array(val_x_padded)\n",
    "\n",
    "train_y_prepared = np.array(train_y)\n",
    "val_y_prepared = np.array(val_y)\n",
    "\n",
    "print('The data is prepared for training!\\n')\n",
    "\n",
    "# Fit the model\n",
    "print('Training:')\n",
    "history = model.fit(train_x_prepared, train_y_prepared, epochs=20, validation_data=(val_x_prepared, val_y_prepared))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab323967",
   "metadata": {},
   "source": [
    "<a name=\"4\"></a>\n",
    "## 4 - Evaluate the model\n",
    "\n",
    "Now that you trained the model, it is time to look at its performance. While training, you already saw a printout of the accuracy and loss on training and validation sets. To have a better feeling on how the model improved with training, you can plot them below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "547f3ce5",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_metrics(history, metric):\n",
    "    plt.plot(history.history[metric])\n",
    "    plt.plot(history.history[f'val_{metric}'])\n",
    "    plt.xlabel(\"Epochs\")\n",
    "    plt.ylabel(metric.title())\n",
    "    plt.legend([metric, f'val_{metric}'])\n",
    "    plt.show()\n",
    "    \n",
    "plot_metrics(history, \"accuracy\")\n",
    "plot_metrics(history, \"loss\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c18ab524",
   "metadata": {},
   "source": [
    "You can see that already after just a few epochs the model reached very high accuracy on both sets. But if you zoom in, you can see that the performance was still slightly improving on the training set through all 20 epochs, while it stagnated a bit earlier on the validation set. The loss on the other hand kept decreasing through all 20 epochs, which means that the model also got more confident in its predictions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8325ea1e",
   "metadata": {},
   "source": [
    "<a name=\"4-1\"></a>\n",
    "### 4.1 - Predict on Data\n",
    "\n",
    "Now you can use the model for predictions on unseen tweets as `model.predict()`. This is as simple as passing an array of sequences you want to predict to the mentioned method.\n",
    "In the cell below you prepare an extract of positive and negative samples from the validation set (remember, the positive examples are at the beginning and the negative are at the end) for the demonstration and predict their values with the model. Note that in the ideal case you should have another test set from which you would draw this data to inspect the model performance. But for the demonstration here the validation set will do just as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "d712e017",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 64ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[0.88643026],\n",
       "       [0.99411005],\n",
       "       [0.99694365],\n",
       "       [0.9484869 ],\n",
       "       [0.9976331 ],\n",
       "       [0.9959706 ],\n",
       "       [0.99179745],\n",
       "       [0.9789474 ],\n",
       "       [0.99839216],\n",
       "       [0.9982843 ],\n",
       "       [0.0108135 ],\n",
       "       [0.04201312],\n",
       "       [0.01325124],\n",
       "       [0.01707425],\n",
       "       [0.01778767],\n",
       "       [0.00640859],\n",
       "       [0.01607126],\n",
       "       [0.00834147],\n",
       "       [0.02312498],\n",
       "       [0.03234838]], dtype=float32)"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Prepare an example with 10 positive and 10 negative tweets.\n",
    "example_for_prediction = np.append(val_x_prepared[0:10], val_x_prepared[-10:], axis=0)\n",
    "\n",
    "# Make a prediction on the tweets.\n",
    "model.predict(example_for_prediction)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "043a206e",
   "metadata": {},
   "source": [
    "You can see that the first 10 numbers are very close to 1, which means the model correctly predicted positive sentiment and the last 10 numbers are all close to zero, which means the model correctly predicted negative sentiment."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7c90d18",
   "metadata": {},
   "source": [
    "<a name=\"5\"></a>\n",
    "## 5 - Test With Your Own Input\n",
    "\n",
    "Finally you will test with your own input. You will see that deepnets are more powerful than the older methods you have used before. Although you go close to 100 % accuracy on the first two assignments, you can see even more improvement here. \n",
    "\n",
    "<a name=\"5-1\"></a>\n",
    "### 5.1 - Create the Prediction Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "9da31016",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "def get_prediction_from_tweet(tweet, model, vocab, max_len):\n",
    "    tweet = process_tweet(tweet)\n",
    "    tweet = padded_sequence(tweet, vocab, max_len)\n",
    "    tweet = np.array([tweet])\n",
    "\n",
    "    prediction = model.predict(tweet, verbose=False)\n",
    "    \n",
    "    return prediction[0][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf2d7208",
   "metadata": {},
   "source": [
    "Now you can write your own tweet and see how the model predicts it. Try playing around with the words - for example change `gr8` for `great` in the sample tweet and see if the score gets higher or lower. \n",
    "\n",
    "Also Try writing your own tweet and see if you can find what affects the output most."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "f48c7ff0",
   "metadata": {
    "deletable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model prediction on unseen tweet: 0.7443742752075195\n"
     ]
    }
   ],
   "source": [
    "unseen_tweet = '@DLAI @NLP_team_dlai OMG!!! what a daaay, wow, wow. This AsSiGnMeNt was gr8.'\n",
    "\n",
    "prediction_unseen = get_prediction_from_tweet(unseen_tweet, model, vocab, max_len)\n",
    "print(f\"Model prediction on unseen tweet: {prediction_unseen}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b35eaaa",
   "metadata": {},
   "source": [
    "<a name=\"ex-8\"></a>\n",
    "### Exercise 8 - graded_very_positive_tweet\n",
    "**Instructions:** For your last exercise in this assignment, you need to write a very positive tweet. To pass this exercise, the tweet needs to score at least 0.99 with the model (which means the model thinks it is very positive).\n",
    "\n",
    "Hint: try some positive words and/or happy smiley faces :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "2f075af5",
   "metadata": {
    "deletable": false,
    "scrolled": true,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# GRADED VARIABLE: graded_very_positive_tweet\n",
    "\n",
    "### START CODE HERE ###\n",
    "\n",
    "# Please replace this sad tweet with a happier tweet\n",
    "graded_very_positive_tweet = 'sad'\n",
    "\n",
    "### END CODE HERE ###"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1420a67",
   "metadata": {},
   "source": [
    "Test your positive tweet below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "8c2fe677",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The model thinks your tweet is not positive enough.\n",
      "Try figuring out what makes some of the tweets in the validation set so positive.\n"
     ]
    }
   ],
   "source": [
    "# Test your graded_very_positive_tweet tweet\n",
    "prediction = get_prediction_from_tweet(graded_very_positive_tweet, model, vocab, max_len)\n",
    "if prediction > 0.99:\n",
    "    print(\"\\033[92m All tests passed\")\n",
    "else:\n",
    "    print(\"The model thinks your tweet is not positive enough.\\nTry figuring out what makes some of the tweets in the validation set so positive.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b6f86ff",
   "metadata": {},
   "source": [
    "<a name=\"6\"></a>\n",
    "## 6 - Word Embeddings\n",
    "\n",
    "In this last section, you will visualize the word embeddings that your model has learned for this sentiment analysis task.\n",
    "By using `model.layers`, you get a list of the layers in the model. The embeddings are saved in the first layer of the model (position 0).\n",
    "You can retrieve the weights of the layer by calling `layer.get_weights()` function, which gives you a list of matrices with weights. The embedding layer has only one matrix in it, which contains your embeddings. Let's extract the embeddings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "4b437a60",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weights of embedding layer have shape: (9535, 16)\n"
     ]
    }
   ],
   "source": [
    "# Get the embedding layer\n",
    "embeddings_layer = model.layers[0]\n",
    "\n",
    "# Get the weights of the embedding layer\n",
    "embeddings = embeddings_layer.get_weights()[0]\n",
    "\n",
    "print(f\"Weights of embedding layer have shape: {embeddings.shape}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f289857c",
   "metadata": {},
   "source": [
    "Since your embeddings are 16-dimensional (or different if you chose some other dimension), it is hard to visualize them without some kind of transformation. Here, you'll use scikit-learn to perform dimensionality reduction of the word embeddings using PCA, with which you can reduce the number of dimensions to two, while keeping as much information as possible. Then you can visualize the data to see how the vectors for different words look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "9f064556",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [],
   "source": [
    "# PCA with two dimensions\n",
    "pca = PCA(n_components=2)\n",
    "\n",
    "# Dimensionality reduction of the word embeddings\n",
    "embeddings_2D = pca.fit_transform(embeddings)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a957d815",
   "metadata": {},
   "source": [
    "Now, everything is ready to plot a selection of words in 2d. Dont mind the axes on the plot - they point in the directions calculated by the PCA algorithm. Pay attention to which words group together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "9696170b",
   "metadata": {
    "deletable": false,
    "editable": false,
    "tags": [
     "graded"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selection of negative and positive words\n",
    "neg_words = ['bad', 'hurt', 'sad', 'hate', 'worst']\n",
    "pos_words = ['best', 'good', 'nice', 'love', 'better', ':)']\n",
    "\n",
    "#Index of each selected word\n",
    "neg_n = [vocab[w] for w in neg_words]\n",
    "pos_n = [vocab[w] for w in pos_words]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "#Scatter plot for negative words\n",
    "plt.scatter(embeddings_2D[neg_n][:,0], embeddings_2D[neg_n][:,1], color = 'r')\n",
    "for i, txt in enumerate(neg_words): \n",
    "    plt.annotate(txt, (embeddings_2D[neg_n][i,0], embeddings_2D[neg_n][i,1]))\n",
    "\n",
    "#Scatter plot for positive words\n",
    "plt.scatter(embeddings_2D[pos_n][:,0], embeddings_2D[pos_n][:,1], color = 'g')\n",
    "for i, txt in enumerate(pos_words): \n",
    "    plt.annotate(txt,(embeddings_2D[pos_n][i,0], embeddings_2D[pos_n][i,1]))\n",
    "\n",
    "plt.title('Word embeddings in 2d')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bca33cce",
   "metadata": {},
   "source": [
    "As you can see, the word embeddings for this task seem to distinguish negative and positive meanings. However, similar words don't necessarily cluster together, since you only trained the model to analyze the overall sentiment. Notice how the smiley face is much further away from the negative words than any of the positive words are. It turns out that smiley faces are actually the most important predictors of sentiment in this dataset. Try removing them from the tweets (and consequently from the vocabulary) and see how well the model performs then. You should see quite a significant drop in performance."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9791af3a",
   "metadata": {},
   "source": [
    "**Congratulations on finishing this assignment!**\n",
    "\n",
    "During this assignment you tested your theoretical and practical skills by creating a vocabulary of words in the tweets and coding a neural network that created word embeddings and classified the tweets into positive or negative. Next week you will start coding some sequence models!\n",
    "\n",
    "**Keep up the good work!**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3babb18",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "grader_version": "1",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}