Work for Scrapshut which was part of Design and Analysis of Software Systems Course at IIIT Hyderabad.
Client : Mounikesh Thadda, Founder of Scrapshut
Mentor TA : Mohit Chandra
To develop a web platform for ScrapShut where users can come and rate different URLs and get reviews of other users on a particular URL. This web app aims to provide users with data on the credibility of the content provided by various websites, to curb fake news perpetration.
We predict the genuineness of a website based on the majority of user ratings, and ML model trained using features like website’s scraped data, user's ratings/ reviews data from the website. Users further would be asked to tell which portions of the article made them think the article is fake and provide basis for their report . We aim to provide users with data on which websites are genuine and not genuine and protect the users malicious websites and fraud.
- Editor - VS Code
- Web framework - Django 3
- Collaboration tools - Gitlab
- Frontend - Angular.js
- Documentation - Google Docs
- Database – AWS, Heroku
- Machine Learning - Keras, Tensorflow, Scipy
- Web Scraping - BeautifulSoup
- Language: Python○ Framework: Jupyter Notebook
- Responsive WebApp
- User login- Signup
- Homepage
- Dashboard
- User Review form
- Check URL verification
- Scraping
- Title, body and all associated links on that page scraped and stored.
- ML model: for classification and prediction whether news is real/fake
- LSTM
- Passive Aggressive Classifier
- CNN
- Real time Classification
- Prediction based on combination of User reviews for that URL and ML models predictions