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A Web Browser Extension to detect the presence of various Dark Patterns on the e-commerce platforms and more using JavaScript, Python, TypeScript, Batchfile, Shell, HTML, CSS, etc.

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krishbtyagi/DPbuster

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Dark Pattern Recognition This web browser extension “DPbuster”, is intended to help consumers to navigate the internet in a way similar to an ad blocker. However, the highlighter differs from ad blockers in one crucial aspect: it does not block individual dark patterns on websites but highlights them so that consumers become aware of the influences affecting them. In addition, the tool informs about the type of pattern.

Additional Features: –

No Blocking of Web Page Content: The extension ensures that it does not block web page content, allowing users to access information while still benefiting from dark pattern detection.

Extension Icon Displaying Number of Detected Dark Patterns: The extension icon dynamically displays the number of detected dark patterns, providing users with a quick visual indicator of potential issues on the webpage.

Function to Individually Highlight Each Detected Dark Pattern: Users have the ability to individually highlight each detected dark pattern out of the 9 famous and profound type of dark patterns.


Installation Instructions

To set up the extension, you need to download either the repository or the chrome folder. Since the extension isn't available in the browser stores, it must be installed in developer mode for browsers. Follow the specific steps outlined below for various tested browsers.

For Chrome:

  1. Open the Extensions page by typing chrome://extensions in a new tab. Alternatively, click the puzzle-shaped Extensions menu button and choose Manage Extensions at the bottom of the menu. Alternatively, click the Chrome menu, hover over More Tools, and then select Extensions.

  2. Enable Developer Mode by toggling the switch next to Developer mode.

  3. Click the Load unpacked button and choose the chrome directory.

  4. (Optional): To permanently display the Pattern Highlighter icon, click the Extensions menu puzzle button in the address bar and then click the Pin button.

For Edge:

Access the Extensions page by typing edge://extensions in a fresh tab. Alternatively, click the Settings and more (...) button, choose Extensions, and select Manage extensions from the displayed popup. Activate Developer Mode by toggling the switch next to Developer mode. Utilize the Load unpacked button to choose the chrome directory. Optionally, click the Extensions menu puzzle button in the address bar, and then select the Show in Toolbar button (eye icon) next to the Pattern Highlighter to ensure its icon is always visible.

For Opera:

Visit the Extensions page by typing opera://extensions in a new tab, or utilize the Cmd/Ctrl + Shift + E shortcut. Activate Developer Mode by toggling the switch adjacent to Developer mode. Press the Load unpacked button and choose the chrome directory. Optionally, click the Extensions menu cube button in the address bar and subsequently hit the Pin button next to the Pattern Highlighter to ensure its icon remains visible permanently.

Tech Stack Used:-

  1. NLP model- Logistic Regression, SVM, Random Forest, Gradient Boosting
  2. Web Extension- HTML, CSS, JS
  3. Deep Learning Python Frameworks: Pytorch, Tensorflow, Keras.
  4. Hardware: 16 GB RAM, Intel i5 12th gen 512 SSD, Windows OS/ MAC OS- M2 pro
  5. IDE- Google Collab and VS code
  6. Dataset Information: The dataset.tsv file located in this directory serves as the dataset for automatically detecting text-based dark patterns.
  7. We have done experimental code of baseline evaluation using classical NLP methods and transformer-based pre-trained language models.
  8. Scraping Section: This directory contains the code designed to gather non-dark pattern texts for inclusion in the dataset.

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A Web Browser Extension to detect the presence of various Dark Patterns on the e-commerce platforms and more using JavaScript, Python, TypeScript, Batchfile, Shell, HTML, CSS, etc.

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