📈 Stock News Sentiment Analysis

Analyze the real-time sentiment of stock market news using Python, FinViz scraping, and VADER sentiment analysis. This project provides both tabular data and visual sentiment charts for multiple tickers in a live web app built with Streamlit.

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🔗 Live Demo

Click here to access the live app

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Snaps

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🚀 Features

• Scrapes real-time news headlines from FinViz for multiple stock tickers.
• Performs sentiment analysis using the VADER lexicon.
• Computes daily average sentiment per ticker.
• Displays interactive tables and bar charts in a web browser.
• Built with Python, Streamlit, Pandas, and Matplotlib.
• Ready for live deployment on Streamlit Cloud.

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🛠 Tech Stack

• Python 3.11+
• Streamlit — web interface
• Pandas — data processing
• Matplotlib — visualization
• BeautifulSoup4 & Requests — web scraping
• NLTK & VADER — sentiment analysis

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💡 How to Use Locally

Clone the repo

git clone https://github.com/your-username/stock-news-sentiment-analysis.git
cd stock-news-sentiment-analysis

pip install -r requirements.txt

streamlit run app.py

Stock-News-Sentiment-Analysis/
│
├── app.py                 # Streamlit web app
├── main.py                # Original CLI script
├── vader_lexicon.txt      # VADER lexicon for sentiment analysis
├── requirements.txt       # Python dependencies
├── README.md              # Project overview
└── LICENSE                # Open source license

⚡ Notes

Streamlit Cloud automatically updates the app whenever you push to GitHub.

FinViz may occasionally block requests — in that case, wait a few minutes and try again.

The VADER lexicon is included to avoid runtime download issues in cloud deployment.

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📈 Future Enhancements

Add historical trend analysis for multiple tickers.

Include sentiment heatmaps and ticker comparisons.

Implement user authentication for personalized watchlists.

Add export to CSV/Excel functionality.