What it does
Our Chrome web-extension reads content held on websites and uses and algorithm to determine whether it's reliable or not. The algorithm uses Fact-checker API and database technologies. We can also feed in statements, which the extension will determine whether the statement is true, relatively bias or bias.
How we built it
Through VSCode, where we used HTML and CSS to code and style the web-extension side-panel, JavaScript to add functionality to the extension. Python has also been used to create a Natural Language Processing Model (NLP model).
Challenges we ran into
Considering this was our first Hackathon, we did encounter many hurdles. However, with enough time and effort we were able to overcome these challenges.
Accomplishments that we're proud of
-The fact-checking algorithm was quite successful and can score websites to a degree.
- Learnt new and developed already existing programming skills.
What we learned
- CSS
- HTML
- JSON Files
- API's
- Model training
- How to build a web ext.
- JavaScript
What's next for Clarity
- General improvements to the style and design of the web extension.
- Inclusion and development of more complex AI to give more in-depth analysis.
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