Advanced Sentiment Analysis

This project compare different advances techniques for Sentiment Analysis in Spanish Tweets using data samples of Sepln-TASS

TASS 2017 (Development)

Model	Macro F1	Accuracy
CNN	0.330	0.77075
SIF	0.733	0.773
ULMFit	0.222	0.3837

TASS 2018

Test

Model	Run	Macro F1	Accuracy
CNN	cnn-btf-2019_03_13-04_12_55	0.387	0.432
SIF	SIF-M LP-2019_01_30-00_27_52	0.399	0.398
ULMFit	md3-2019_03_12-06_37_15	0.270	0.299

Development

Model	Accuracy
CNN	0.755
SIF	0.602
ULMFit	0.309

Extras

Word2Vec embeddings from SBWC

Embeddings

Links to the embeddings (#dimensions=300, #vectors=1000653)

• Vector format (.txt.bz2)
• Binary format (.bin.gz)

Algorithm

• Implementation: Word2Vec with Skipgram by GenSim
• Parameters: For details on parameters please refer to the SBWCE page

Corpus

• Spanish Billion Word Corpus
• Corpus Size: 1.4 billion words

Reference

Word embeddings were computed by Cristian Cardellino. Please refer to the SBWCE page if you want to use these vectors.