comparitive sentiment analysis of financial and political subreddits

project inspiration

With social media platforms now driven by algorithms tailored to each user’s experience, it can be hard to gauge the overall sentiment of users. Last year, I became increasingly curious about whether the recession discussions I was seeing across my LinkedIn, Reddit, and X feeds were based in reality or just a small subset of users that my algorithm kept feeding me. I realized that one way to investigate this, while also honing my data analysis skills, was to conduct a comparative sentiment analysis across various political and economic subreddits. If the political and economic subreddits matched each other in terms negative sentiment, perhaps further analysis into recession-specific topics could allow for stronger insight. If the political subreddits are significantly higher in negative sentiment than economic subreddits, perhaps the discussion of recession is more speculative than rooted in material reality. This isn’t exactly a “wisdom of the crowds” experiment, as social media often rewards outrage, which can skew objectivity. Instead, it’s an attempt to explore the broader sentiment of a larger user base, beyond the filtered content of a personalized feed. It is important to note, however, that VADER’s compound scores may not always capture the nuances of human language.

steps taken

Firstly, I compared overall sentiment differences between the political subreddits (r/news, r/politics, r/geopolitics) with the economic subreddits (r/stocks, r/jobs, r/economics). Then, I sought after a more granular level of analysis by investigating whether each category of sentiment (negative, neutral, positive) was significantly different across the political and economic subreddits.

results

Here are my results reran in January 2025:

data data data

code

You can view the code for this project on my github found here.

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