Fake News Detection System

A full-stack application combining a DistilBERT-based classification model with fact-checking capabilities and explainable AI (XAI) features.

Features

• 🧠 DistilBERT model for real/fake news classification
• 🔍 Integrated Google Fact Check API verification
• 📊 LIME (Local Interpretable Model-agnostic Explanations) for predictions
• 📈 Confidence metrics and probability distributions
• 💾 Feedback system for model improvement
• 🌓 Dark mode support
• 📚 Search history tracking

Technologies

Backend:

• Python/Flask
• Transformers (DistilBERT)
• LIME
• Google Fact Check API

Frontend:

• React.js
• CSS3 (with CSS Variables)
• React Icons

Installation

Backend Setup

1. Clone the repository

   git clone https://github.com/pulk17/Fake-News-Detector
   cd Fake-News-Detector
   

2. Install Python dependencies

   pip install -r requirements.txt
   

3. Environment Variables

   Create .env file:

   FACT_CHECK_API_KEY=your_google_api_key
   FLASK_APP=app.py
   

4. Setting up Frontend

   Make sure node is installed on your device.

   cd fake-news-detector
   npm install
   npm run dev
   

5. Setting up backend

   Make sure you have python installed and have installed the dependencies (Step 2). Open a new terminal.

   cd Fake-News-Detector
   flask run --host=0.0.0.0 --port=5000