• Frontend: https://reddit-dashboard-one.vercel.app/
• Backend API: https://reddit-dashboard-purple-hill-3043.fly.dev/

A comprehensive full-stack application for analyzing Reddit data using AI-powered insights, interactive visualizations, and real-time analytics. The platform provides deep insights into social media trends, sentiment analysis, and user engagement patterns.

https://drive.google.com/file/d/1H48_XLk1vdFovn049T3iJLWT9CJ7S9CJ/view?usp=drive_link

• Real-time sentiment analysis
• Topic modeling and trend detection
• Engagement pattern analysis
• Content quality assessment
• AI-driven recommendations

• Time series analysis
• Network graphs
• Heat maps
• Word clouds
• Interactive charts

• Responsive Material UI design
• Dark/Light theme support
• Real-time updates
• Interactive filters
• Cross-platform compatibility

• Next.js 14
• TypeScript
• Material-UI (MUI)
• React Query
• Plotly.js
• React Force Graph

• Python 3.12
• Flask
• DuckDB
• NLTK
• scikit-learn
• Google Gemini AI
• Flask-CORS

• Vercel (Frontend)
• Fly.io (Backend)
• Docker
• GitHub Actions

/
├── backend/                # Flask backend service
│   ├── app.py             # Main application file
│   ├── data/              # Data storage
│   └── requirements.txt   # Python dependencies
├── social-media-dashboard/ # Next.js frontend
│   ├── src/               # Source code
│   └── public/            # Static assets
├── tests/                 # Integration & unit tests
└── README.md             # Main documentation

• Node.js 18+
• Python 3.12+
• Docker (optional)

cd social-media-dashboard
npm install --legacy-peer-deps
npm run dev

cd backend
python -m venv venv
source venv/bin/activate  # or `venv\Scripts\activate` on Windows
pip install -r requirements.txt
python app.py

Create .env.local for frontend:

NEXT_PUBLIC_API_URL=http://localhost:5000

Create .env for backend:

GEMINI_API_KEY=your_api_key_here

• /api/health - Health check
• /api/stats - Basic statistics
• /api/sentiment - Sentiment analysis
• /api/network - Network analysis
• /api/topics - Topic modeling
• /api/timeseries - Time series data
• /api/ai/insights - AI-powered insights

• Backend API Documentation
• Frontend Documentation
• Testing Documentation

cd social-media-dashboard
vercel deploy

cd backend
fly deploy

# Run frontend tests
cd social-media-dashboard
npm test

# Run backend tests
cd backend
pytest

# Run integration tests
cd tests
pytest

• CORS configuration
• Rate limiting
• Input validation
• Error handling
• API key protection

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

This project is licensed under the MIT License.

• Sarthak Bhardwaj

• Material-UI for the component library
• Flask for the backend framework
• Next.js for the frontend framework
• Vercel and Fly.io for hosting