https://github.com/anantduhan/web-behaviour-detection

A browser extension that uses sentiment analysis to make your web more positive by reducing negative content visibility.
https://github.com/anantduhan/web-behaviour-detection

chrome-extension ci javascript python sentiment web-extension wellbeing

Last synced: 7 months ago
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A browser extension that uses sentiment analysis to make your web more positive by reducing negative content visibility.

• Host: GitHub
• URL: https://github.com/anantduhan/web-behaviour-detection
• Owner: AnantDuhan
• Created: 2022-09-22T09:12:30.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-10-27T07:37:29.000Z (almost 3 years ago)
• Last Synced: 2025-01-07T01:09:26.491Z (9 months ago)
• Topics: chrome-extension, ci, javascript, python, sentiment, web-extension, wellbeing
• Language: JavaScript
• Homepage:
• Size: 1.06 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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# Web Behaviour Detection:

Use sentiment analysis to reduce negative content visibility to make your web more positive.

## What does this do?

A browser extension that finds negative elements on the page and makes them less visible:

- Negativity is calculated using either inin-browserule-based logic or an **optional** deep learning model running locally in the background (in a docker container).

- The user controls various options (negativity threshold, restyling options) via the options menu:

    - Visibility is reduced by adjusting transparency, or by hiding the element completely.

    - Colours can be added for inspection, or for examining the positivity.

    - Settings can be saved per site or globally.

    - An overall positivity score per page is displayed.

## Sentiment "Scoring" options:

1. Use `Vader (JS)` or `AFINN (JS)` in the drop-down for browser side, rule-based calculations.

2. For the `FlairNLP (Py)` option a local python inference server needs to be running:

    Running in docker (simplest if you have docker)

    > Please wait a few seconds after starting to be ready to serve requests.

    Run interactively once (e.g to try it out):

    - Start: `docker run -p 8000:8000 -it --rm anantduhan/web-behaviour-detection`

    - Stop just Ctrl+C in the terminal where you're running it.

    Run in detached and persistent mode (e.g. for actual usage):

    - Start: `docker run -p 8000:8000 -dit --restart unless-stopped --name web-behaviour-detection anantduhan/web-behaviour-detection`

    - Stop: `docker rm -f web-behaviour-detection`.

    Local python (e.g. for development)

    1. Clone repo.

    2. `make install` to create a local virtual environment and install dependencies in it. 

    3. `make server` to run the server. 

## Using local extension

### Build

Building instructions

- Clone and go to the `extension/` folder:

- To install in the local environment: `npm install`

- Building: `npm start` for development, `npm run build` for packaging into a zip file.

### Load browser extension into Chrome or Firefox:

Chrome

- Extensions -> Enable "developer mode" -> 

"Load unpacked extensions" -> Navigate to `/extension/dist` folder in this project.

- To update (on code changes): go to extension details and press update / reload.

- Docs: [Chrome docs](https://developer.chrome.com/extensions/getstarted#manifest)

Firefox

- To load for development (will be removed after browser close, but easier to reload on code change):

    - Go to `about:debugging` -> This Firefox -> "Load Temporary Add-on.." -> 

    Navigate to `/extension/dist` -> select manifest file.

    - Press "Reload" to update on code changes.

- To load for continuous usage (persistent after closing):

    - Go to `about: config` and set `xpinstall.signatures.required` to False to be able to load a local extension.

    - Run `npm run-script build` to package the extensions into a zip file.

    - Go to `about:addons` -> "gear" icon -> "Install add-on from file.." -> 

    Navigate to `/extension/` folder in this project -> choose `web-behaviour-detection-.zip`.

    - To update (on code changes): repeat the previous two steps.

- Docs: [Firefox docs](https://extensionworkshop.com/documentation/develop/testing-persistent-and-restart-features/)

## Credits and references:

- Python (DL-based) sentiment analysis model and package: [flair NLP](https://github.com/flairNLP/flair)

- JS sentiment analysis packages:

    - [vaderSentiment](https://github.com/cjhutto/vaderSentiment) (called JS-Vader in options menu)

    - [AFINNSentiment](https://github.com/thisandagain/sentiment ) (called JS-AFINN in options menu)

- Backend API framework: [fastapi](https://github.com/tiangolo/fastapi)

- Initial code for browser extension functionality copied from [Trump-Filter](https://github.com/RobSpectre/Trump-Filter)