Reddit Sentiment Analyzer

Reddit Sentiment Analyzer is a web-based application that allows users to analyze the sentiment of Reddit comments in real-time or from pre-analyzed datasets. It provides a comprehensive dashboard with visualizations for sentiment distribution, emotion detection, keyword analysis, and topic extraction.

Features

• Live Analysis: Analyze Reddit comments for any topic and subreddit in real-time.
• Pre-Analyzed Datasets: Explore sentiment patterns from pre-scraped Reddit comments on various topics.
• Sentiment Distribution: View the breakdown of comments into positive, negative, and neutral sentiments.
• Emotion Detection: Identify emotions such as joy, anger, sadness, fear, and surprise in the comments.
• Keyword Analysis: Discover the most frequently used keywords for each sentiment category.
• Topic Extraction: Automatically extract the main discussion topics from the comments.
• Interactive Dashboard: Visualize the analysis results with interactive charts and graphs.
• Dark Mode: Switch between light and dark themes for better viewing comfort.

Tech Stack

Backend

• Flask: A micro web framework for Python.
• PRAW (Python Reddit API Wrapper): For accessing Reddit's API.
• NLTK (Natural Language Toolkit): For sentiment analysis and natural language processing.
• Pandas: For data manipulation and analysis.
• Scikit-learn: For topic extraction using TF-IDF.

Frontend

• HTML, CSS, JavaScript: For the application's structure, styling, and interactivity.
• Bootstrap: A popular CSS framework for building responsive, mobile-first sites.
• Chart.js: For creating interactive charts and graphs.
• Font Awesome: For icons.

Installation and Setup

1. Clone the repository:

   git clone https://github.com/your-username/RedditSentimentAnalyzer.git
   cd RedditSentimentAnalyzer

2. Install the required packages:

   pip install -r requirements.txt

3. Set up Reddit API credentials:

   • Create a Reddit application to get your API credentials.
   • Set the following environment variables:

     REDDIT_CLIENT_ID=your_client_id
     REDDIT_CLIENT_SECRET=your_client_secret
     REDDIT_USER_AGENT=your_user_agent
     

4. Run the Flask application:

   python app.py

   The application will be running at http://localhost:5000.

Usage

1. Choose an analysis mode:

   • Live Analysis: Enter a topic and an optional subreddit to fetch and analyze comments in real-time.
   • Pre-Analyzed Datasets: Select a pre-scraped dataset from the dropdown to explore existing analysis.

2. View the results: The dashboard will display various visualizations, including:

   • Sentiment distribution (doughnut chart and table).
   • Sentiment timeline (line chart).
   • Emotion distribution (polar area chart).
   • Key discussion topics.
   • Word clouds for positive, negative, and neutral keywords.
   • Sample comments for each sentiment.

File Structure

├── app.py                  # Main Flask application
├── requirements.txt        # Python package dependencies
├── frontend/
│   ├── index.html          # Main HTML file for the UI
│   ├── css/style.css       # Custom CSS styles
│   └── js/script.js        # JavaScript for frontend logic
├── data/
│   ├── reddit_comments/    # Directory for pre-scraped CSV datasets
│   └── preprocessed_results/ # Directory for cached analysis results
└── ...

Acknowledgements

• This project utilizes several open-source libraries, including Flask, PRAW, NLTK, Pandas, and Scikit-learn.
• The frontend is built with Bootstrap and Chart.js.