Reddit Stock Sentiment Analyzer

A Flask web application that analyzes recent Reddit discussions for a given stock symbol to gauge public sentiment. It fetches posts, performs sentiment analysis using NLP, filters for quality discussions, and visualizes the sentiment trend.

Features

• Reddit Data Fetching: Retrieves recent posts mentioning a stock symbol from relevant subreddits (e.g., r/stocks, r/wallstreetbets, r/investing).
• Sentiment Analysis: Uses NLTK's VADER to calculate sentiment scores for fetched posts.
• Quality Filtering: Implements a scoring mechanism to filter out low-quality or irrelevant posts based on length, Reddit score, and sentiment intensity.
• Trend Visualization: Generates and displays a plot showing the daily average sentiment trend using Matplotlib.
• Web Interface: Provides a clean, responsive, dark-mode UI built with Flask, HTML, CSS, and JavaScript for easy interaction.

Tech Stack

• Backend: Python, Flask
• Data Fetching: Praw (for Reddit API)
• NLP: NLTK (VADER for sentiment)
• Data Handling: Pandas
• Visualization: Matplotlib
• Frontend: HTML, CSS, JavaScript

Setup

1. Clone the repository (if you haven't already):

   git clone <your-repository-url>
   cd stock # Navigate into the project directory

2. Create a virtual environment (recommended):

   python -m venv venv
   # Activate it:
   # Windows:
   .\venv\Scripts\Activate.ps1
   # macOS/Linux:
   # source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Create a .env file in the project root (stock/) with your Reddit API credentials:

   REDDIT_CLIENT_ID=your_client_id
   REDDIT_CLIENT_SECRET=your_client_secret
   REDDIT_USER_AGENT=your_user_agent_string (e.g., MyStockAnalyzer/0.1 by u/YourUsername)

   (You can get credentials by creating a 'script' app on Reddit: https://www.reddit.com/prefs/apps)

Usage

1. Navigate to the src directory:

   cd src

2. Run the Flask application:

   flask run --host=0.0.0.0

   (The --host=0.0.0.0 makes it accessible on your local network; use 127.0.0.1 or omit for local access only)

3. Open your web browser and go to http://127.0.0.1:5000 (or your machine's IP address if using 0.0.0.0).

4. Enter a stock symbol (e.g., AAPL, TSLA, GME) and click "Analyze".

5. View the sentiment analysis results, trend plot, and top relevant posts.