Market Sentiment Analyzer
Real-time sentiment analysis from news and social media for trading signals
Hero Summary
What
A comprehensive sentiment analysis platform that processes thousands of news articles, tweets, and Reddit posts to gauge market sentiment for individual stocks and the broader market. Uses advanced NLP models to classify text as bullish, bearish, or neutral.
Why
Aggregates sentiment scores from multiple sources and generates a composite sentiment indicator. High positive sentiment triggers long signals, while high negative sentiment suggests short opportunities. The system includes anomaly detection to identify unusual spikes in sentiment that often precede significant price movements.
Result
accuracy
78%
sources
50+
updates
Real-time
symbols
500+
System Overview
How It Works
Aggregates sentiment scores from multiple sources and generates a composite sentiment indicator. High positive sentiment triggers long signals, while high negative sentiment suggests short opportunities. The system includes anomaly detection to identify unusual spikes in sentiment that often precede significant price movements.
Technologies Used
Technical Implementation
Uses FinBERT transformer model for financial sentiment classification. Data is collected via Twitter API, Reddit API, and news RSS feeds. Real-time processing pipeline built with Python and WebSocket connections. React frontend displays live sentiment dashboards with historical trends.
Trade Examples & Visualizations
Visual examples of the strategy in action, showing entry/exit points, equity curves, and market behavior.
Limitations & Failure Modes
Every strategy has weaknesses. Here are the known limitations and scenarios where this system struggles.
Filtering out spam and bot-generated content
Handling multiple languages and slang
Managing API costs and rate limits
Key Learnings
Sentiment doesn't always correlate with price movements - sometimes extreme positive sentiment indicates a market top. I learned to use sentiment as a contrarian indicator in certain market conditions. API rate limits also required implementing efficient data collection strategies.
Future Improvements
Planned enhancements and next steps for this project.
Add support for earnings call transcripts
Implement custom trained models for specific sectors
Create alerts for sentiment anomalies
Build historical sentiment database
Quick Info
Category
Analysis Tool
Status
In DevelopmentTech Stack
Links
Source Code