Fake News and Fake Profile Detection using Machine Learning

The increasing development of disinformation and fake social media profiles, threatens, online safety, trust, and communication. Fake news misguides the public, while fake profiles enable scams, impersonation, and cybercrimes. To manage these challenges, this project introduces a dual-module Machine Learning system that detects both fake news and un-authorized user profiles. A using NLP technique like TF-IDF and ML models such as Logistic Regression and Random Forest, the system distinguish news as real or fake and analyzes profile metadata for authenticity. A Streamlit-based web app provides fast, automated, and user-friendly predictions to enhance online security and reduce harmful digital content and reduce cyber attacks.