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This is a simple Python script that utilizes the PRAW library to scrape comments from a specified subreddit on Reddit, analyzes the sentiment of the comments using both TextBlob and VADER (NLTK's sentiment analysis tool)

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Reddit Sentiment Analysis

Overview

This is a simple Python script that utilizes the PRAW library to scrape comments from a specified subreddit on Reddit, analyzes the sentiment of the comments using both TextBlob and VADER (NLTK's sentiment analysis tool), and exports the results to an Excel file.

Required dependencies

  • Python 3.x
  • PRAW (pip install praw)
  • pandas (pip install pandas)
  • TextBlob (pip install textblob)
  • NLTK (pip install nltk)

Output

The script provides sentiment analysis using both TextBlob and VADER. It categorizes comments as Positive, Negative, or Neutral and exports the results to an Excel file for further analysis.

Acknowledgments

  • PRAW: The Python Reddit API Wrapper
  • NLTK: Natural Language Toolkit
  • TextBlob: Simplified Text Processing

Feel free to contribute, report issues, or suggest improvements!

Rationale...

This concept started when I wanted to find subjects to up my WAM for my uni degree... So I decided to experiment with a straightforward sentiment analysis approach, focusing on posts related to a particular subject within the r/unimelb subreddit. The goal was to gauge the majority sentiments and opinions on a specific subject within the university community :)

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This is a simple Python script that utilizes the PRAW library to scrape comments from a specified subreddit on Reddit, analyzes the sentiment of the comments using both TextBlob and VADER (NLTK's sentiment analysis tool)

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