Subreddit Vibes

Inspiration

We wanted to know which university had the most unhappy students.

What it does

• Evaluates the overall sentiments of comments for one or multiple posts of a subreddit on Reddit.
• Compares the vibes of two different subreddits, based on the most recent or top posts.

How we built it

1. Scrape comments from Reddit using BeautifulSoup4.
2. Classify the overall sentiment of a comment as "Positive", "Negative", or "Neutral" using Python's NLTK library.
3. Visualize the "vibes" of a subreddit through pie charts, histograms and grouped bar charts using Matplotlib.

Challenges we ran into

• Figuring out how to do web scraping
• Fixing git merge errors

Accomplishments that we're proud of

• Web scraping for the first time!
• Proving that, as expected, students at McGill are slightly more miserable than those at Concordia.

What we learned

• Web scraping in Python using BeautifulSoup
• Using GitHub to collaborate with others on a project

What's next for Subreddit Vibes

• Train our own data to get results that better correspond to what we want to investigate
• Evaluate other data sources, like Twitter tweets and customer reviews.
• Compare the vibes of more than 2 subreddits to get THE best university subreddit

Built With

• beautiful-soup
• matplotlib
• nltk
• python
• requests
• scrape