Dark Pattern Research

A tool used for an university project work to conduct a web investigation among the most popular italian websites with the scope to find possible usage of deceptive design in the cookie banners.

Project organization

├── data
│   ├── csv_files
│   ├── results
│   └── screenshots
│       ├── detected_banners
│       └── visited_websites
└── utilities
    ├── search_handlers
    ├── __init.py
    ├── BannerDetector.py
    ├── ButtonElement.py
    ├── dark_pattern_heuristics.py
    ├── .gitignore
    └── README.md
    

Requirements

Requirements can be installed by using the command

pip install -r requirements.txt

Getting started

The tool has three main functionalities: - detection of a banner in a website; - scraping of elements contained in a banner; - performing an analysis on the collected data, in order to find possible violations.

To start the tool is enough executing the main.py by the command

python3 main.py

Before doing this, according to the analysis to perform, it's necessary to call the specific methods.

Banner detection

To perform the detection of banners off a list of websites, call in main.py the method

startBannerDetection()

In the file BannerDetector, specify the name of the list (csv format) of websites to analyze.

Banner scraping

Firstly, you have to set up the backend in order to store the collected elements from the banner. Get the backend here -> https://github.com/simtape/dark-pattern-backend and follow the instruction in the README to set it up. To perform the scraping of elements off banners, call in main.py the method

startButtonDetection()

In the file BannerDetector, specify the name of the list (csv format) of websites to analyze.

Analysis of data

To perform the detection of deceptive elements and so the production of results, call in main.py the method

start_analysis(<your_address_of_localhost_backend>)

Before starting the analysis, fire up the backend locally.