| --- |
| title: Misinformation Heatmap |
| emoji: 🛡️ |
| colorFrom: yellow |
| colorTo: green |
| sdk: docker |
| pinned: true |
| --- |
| |
| # 🛡️ Misinformation Heatmap |
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| A comprehensive AI-powered system for detecting misinformation in Indian media using advanced machine learning, IndicBERT, satellite verification, and fact-checking integration. |
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| [](LICENSE) |
| [](https://www.python.org/downloads/) |
| [](https://fastapi.tiangolo.com/) |
|
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| --- |
|
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| ## 📸 Screenshots & Demo |
|
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| ### Main Homepage |
| > Overview of the whole website |
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|  |
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| ### Main Dashboard |
| > Real-time misinformation detection dashboard with live statistics |
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|  |
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| ### Interactive India Heatmap |
| > Geographic visualization of misinformation distribution across Indian states |
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|  |
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| ### 🎥 Video Demo |
| > Full system walkthrough and feature demonstration |
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| [](https://youtube.com/your-video-link) |
| *Coming Soon* |
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|
| --- |
|
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| ## 🚀 Key Features |
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| - **Advanced AI Analysis**: 5-model ensemble ML classifier (91.0% accuracy, 0.973 ROC-AUC, 91.0% CV F1) |
| - **IndicBERT Integration**: Indian language embeddings for cultural context |
| - **Deterministic Detection**: Removed all random simulations for reproducible results |
| - **Real-time Processing**: 34+ Indian news sources with live RSS ingestion |
| - **Interactive Visualization**: State-wise heatmap with geographic distribution |
| - **Multi-layer Verification**: Fact-checking database, satellite geocoding, source credibility |
| - **Indian Context**: Specialized for Hinglish, regional languages, WhatsApp forwards |
| - **940-Example Dataset**: Vibrant misinformation dataset (477 fake / 463 real) with 6 source types |
| - **RESTful API**: Comprehensive API with Swagger documentation |
| - **Docker Support**: Easy deployment with Docker Compose |
| - **Scalable Architecture**: Handles high-volume data ingestion |
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| --- |
|
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| ## 🚀 Quick Start |
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| ### Prerequisites |
| - Python 3.8 or higher |
| - pip (Python package manager) |
| - Git |
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| ### 1. Clone the Repository |
| ```bash |
| git clone https://github.com/NayandG07/misinformation-heatmap.git |
| cd misinformation-heatmap |
| ``` |
|
|
| ### 2. Install Dependencies |
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
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| ### 3. Set Up Environment Variables (Optional) |
| ```bash |
| # Copy the example environment file |
| cp .env.example .env |
| |
| # Edit .env with your API keys (optional) |
| # GOOGLE_MAPS_API_KEY=your_google_maps_api_key |
| # OPENAI_API_KEY=your_openai_key |
| ``` |
|
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| ### 4. Initialize Database (First Time Only) |
| ```bash |
| cd backend |
| python init_db.py |
| ``` |
|
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| ### 5. Run the System |
| ```bash |
| # From backend directory |
| python main_application.py |
| |
| # Or from project root |
| python backend/main_application.py |
| ``` |
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| The system will be available at **http://localhost:8080** |
|
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| --- |
|
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| ## 🌐 Deployment |
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| ### Docker Deployment (Recommended) |
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| ```bash |
| # Development mode |
| docker-compose up --build |
| |
| # Production mode |
| docker-compose -f docker-compose.prod.yml up -d |
| |
| # Stop services |
| docker-compose down |
| |
| # View logs |
| docker-compose logs -f app |
| |
| # Restart services |
| docker-compose restart |
| ``` |
|
|
| ### Manual Deployment |
|
|
| ```bash |
| # 1. Install dependencies |
| pip install -r requirements.txt |
| |
| # 2. Initialize database |
| cd backend |
| python init_db.py |
| |
| # 3. Run application |
| python main_application.py |
| |
| # 4. Access at http://localhost:8000 |
| ``` |
|
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| ### Production Deployment |
|
|
| ```bash |
| # Using Gunicorn (recommended for production) |
| cd backend |
| gunicorn main_application:app \ |
| -w 4 \ |
| -k uvicorn.workers.UvicornWorker \ |
| --bind 0.0.0.0:8000 \ |
| --access-logfile - \ |
| --error-logfile - |
| |
| # Or use the provided scripts |
| ./scripts/run_local.sh # Local development |
| ./scripts/docker-dev.sh start # Docker development |
| ./scripts/docker-prod.sh deploy # Docker production |
| ``` |
|
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| --- |
|
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| ## 📚 Documentation |
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| Complete documentation is available in the [`docs/`](docs/) folder: |
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| - **[📖 Documentation Index](docs/README.md)** - Complete documentation guide |
| - **[🏗️ Project Structure](docs/PROJECT_STRUCTURE.md)** - Detailed project organization |
| - **[🔧 Backend Architecture](docs/BACKEND_ARCHITECTURE.md)** - System design and components |
| - **[🤖 ML Model Documentation](docs/ML_MODEL_DOCUMENTATION.md)** - AI model specifications |
| - **[🛡️ System Overview](docs/SYSTEM_OVERVIEW.md)** - Complete feature overview |
| - **[🛠️ Scripts Guide](scripts/README.md)** - Development and deployment scripts |
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| --- |
|
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| ## 📝 License |
|
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| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. |
|
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| --- |
|
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| ## 🙏 Acknowledgments |
|
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| - **IndicBERT**: [AI4Bharat](https://ai4bharat.org/) for Indian language models |
| - **News Sources**: 30+ Indian news outlets for real-time data |
| - **Fact-Checkers**: [Alt News](https://www.altnews.in/), [Boom Live](https://www.boomlive.in/), [WebQoof](https://www.thequint.com/news/webqoof) for verification |
| - **Open Source Community**: Built with FastAPI, scikit-learn, PyTorch, and more |
| - **Contributors**: Thanks to all contributors who have helped improve this project |
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| --- |
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| **🛡️ Built for combating misinformation in Indian media** |
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| **Made with ❤️ for a more informed India** |
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| --- |
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| *Last Updated: March 11, 2026* |
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