ML project for the McGill Artificial Intelligence Society's machine learning bootcamp (MAIS 202, Winter 2021). Training data from Kaggle: https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset.
This web app classifies news articles as fake or not given their URL. If the article is deemed fake, it will scrape news sites for trustworthy articles on a similar topic and return the one with the highest topic similarity through Latent Semantic Analysis. Due to limitations of the original dataset, results are not always reliable - use with caution!
This web app is available as a pure Flask web app hosted on Heroku that allows a user to paste in an article's URL to have its reliability judged, and as a Google Chrome extension using the Flask app as a backend that allows a user to check whether or not the current page is a reliable article.
To run the webapp, simply go to https://fake-news-corrector.herokuapp.com and enter the URL of the article you'd like to judge the reliability of. No downloads necessary!
To run the Chrome Extension:
- First download the "ChromeExtension" folder from this Github.
- In Google Chrome, open chrome://extensions and enable "Developer mode" in the top right corner
- Click "Load unpacked" and select the ChromeExtension folder.
- Navigate to the article you'd like to judge the reliability of.
- Click the Fake News Corrector extension in the Extensions bar in the top right of the Google Chrome window to get your results!
-
For the newspaper/Article library, run
pip3 install newspaper3k -
For the News API, run
pip install newsapi-python
Below is a listing of relevant files:
Fake-news-correcter/
├─ ChromeExtension/
│ ├─ manifest.json
│ ├─ popup.html
│ ├─ popup.js
├─ Deliverables/
│ ├─ Data Selection Proposal.pdf
│ ├─ Deliverable2.pdf
│ ├─ Deliverable3.pdf
├─ Models/
│ ├─ BenchmarkModels
│ │ ├─ ...
│ ├─ ...
├─ templates
│ ├─ home.html
│ ├─ fake.html
│ ├─ true.html
├─ app.py
├─ articles.py
├─ predict.py
├─ README.md