What happens when the stock market goes haywire? People turn to Reddit—and this project dives into what they say.

Using data from the most popular stock-related subreddit, this project performs sentiment analysis to understand how retail investors react to major market events. It’s a fascinating intersection of finance, language, and data science.

Project Highlights

  • 🧠 NLP for Finance: Applies Natural Language Processing (NLP) techniques to Reddit posts from r/wallstreetbets.
  • 📈 Market Context: Focuses on periods of market volatility to study emotional and cognitive trends.
  • 🕵️ Sentiment Evolution: Tracks how public sentiment shifts as financial news breaks and market reactions unfold.
  • 📦 End-to-End Pipeline: From data scraping to visualization—all done in Python.

Tech Stack

  • Data Sources: Reddit JSON dumps
  • Text Processing: VADER
  • Stock price forecasting: Scikit-learn
  • Visualization: Matplotlib + Seaborn

Key Insights

  • Weak connection between sentiment and stock price changes in usual market conditions.
  • Sentiment peaks often lag behind major market events—retail reacts, but slowly.

For the full code, visit the GitHub repository