CryptoPulse 📈

A cryptocurrency market sentiment analysis and price prediction platform that combines social media sentiment with historical price data to forecast market movements.

Features

• Real-time social media sentiment analysis (Twitter, Reddit)
• Historical cryptocurrency price analysis
• Advanced price prediction using machine learning
• Interactive dashboard for market insights
• Sentiment trend visualization

Project Structure

CryptoPulse/
├── data/               # Data storage
├── notebooks/          # Jupyter notebooks for analysis
├── src/               # Source code
│   ├── data/          # Data collection and processing
│   ├── models/        # ML models
│   ├── sentiment/     # Sentiment analysis
│   └── visualization/ # Dashboard and plots
├── tests/             # Unit tests
└── webapp/           # Streamlit web application

Setup

1. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

cp .env.example .env
# Edit .env with your API keys

Usage

1. Start the data collection:

python src/data/collector.py

2. Run the sentiment analysis:

python src/sentiment/analyzer.py

3. Launch the web dashboard:

streamlit run webapp/app.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.