Web Positiviser:

Make your web more positive by using sentiment analysis to reduce negative content visibility.

What does this do?

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

• Negativity is calculated using either in browser rule 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.

Installing the extension

• Download for Chrome

• Download for Firefox

• Or build and use from source by following instruction below for "Using local extension".

Sentiment "Scoring" options:

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

2. For 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 artdgn/web-positiviser

   • 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-positiviser artdgn/web-positiviser

   • Stop: docker rm -f web-positiviser.

   Local python (e.g. for development)

   1. Clone repo.
   2. make install to create 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 extension/ folder:
• To install in 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): and go to extension details and press update / reload.
• Docs: Chrome docs

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 Temprorary 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-positiviser.zip.
  • To update (on code changes): repeat previous two steps.
• Docs: Firefox docs

Credits and references:

• Python (DL based) sentiment analysis model and package: flair NLP
• JS sentiment analysis packages:
  • vaderSentiment (called JS-Vader in options menu)
  • AFINNSentiment (called JS-AFINN in options menu)
• Backend API framework: fastapi
• Initial code for browser extension functionality copied from Trump-Filter