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The Fake News Detection System is an AI-powered platform that classifies news articles and videos as real or fake. It allows users to input text or URLs, scrapes the content using BeautifulSoup, and p
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Project Description: Fake News Detection System
This AI-driven Fake News Detection System is designed to verify the authenticity of news articles and videos. It leverages a Multinomial Naive Bayes model trained on labeled datasets to classify input as real or fake. The system supports both text and URL-based input, using BeautifulSoup for content scraping and Scikit-learn for processing and prediction. Additionally, it detects AI-generated videos to prevent the spread of deepfakes. The backend is built using Node.js, Express, and MongoDB, while the frontend leverages React, Vite, and Tailwind CSS for a dynamic user interface. A unique feature includes a browser extension that scans live news feeds in real-time and sends notifications if the content is likely fake. This end-to-end solution aims to combat misinformation and promote media literacy.