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- The post uses sentiment analysis to examine reactions across five political subreddits during the November 8, 2016 US presidential election results.
- The post reports that sentiment on r/hillaryclinton fell as the night progressed while comment volume peaked around 9pm EST, while r/The_Donald showed the opposite pattern.
- The post finds that pro-Trump subreddits showed higher positive sentiment than pro-Clinton subreddits as results came in, while r/PoliticalDiscussion showed no notable shift.
- The post suggests future applications of the same technique, including classifying newspaper comment sections and analyzing sporting events or other losing-candidate communities.
Sentiment Analysis is a powerful Natural Language Processing technique that can be used to compute and quantify the emotions associated with a body of text. One of the reasons that Sentiment Analysis is so powerful is because its results are easy to interpret and can give you a big-picture metric for your dataset.
One recent event that surprised many people was the November 8th US Presidential election. Hillary Clinton, who ended up losing the race, had been given chances ranging from a 71.4% (FiveThirtyEight), to a 85% (New York Times), to a >99% chance of victory (Princeton Election Consortium).
Credit: New York Times
We examined five political subreddits to gauge their reactions. Our first target was /r/hillaryclinton, Clinton’s primary support base. The number of comments reached a high starting at around 9pm EST, but the sentiment gradually fell as news came in that Donald Trump was winning more states than expected.
/r/hillaryclinton: Number of Comments per Hour
/r/hillaryclinton: Mean Sentiment Score per Hour
/r/SandersforPresident /r/Political_Revolution
/r/Political_Revolution: Number of Comments per Hour
/r/Political_Revolution: Mean Sentiment Score per Hour
On /r/The_Donald (Donald Trump’s base), the results were the opposite.
/r/The_Donald: Number of Comments per Hour
/r/The_Donald: Mean Sentiment Score per Hour
There are also a few subreddits that are less candidate- or ideology-specific: /r/politics and /r/PoliticalDiscussion. /r/PoliticalDiscussion didn’t seem to show any shift, but /r/politics did seem to become more muted, at least compared to the previous night.
/r/PoliticalDiscussion: Number of Comments per Hour
/r/PoliticalDiscussion: Mean Sentiment Score per Hour
/r/politics: Mean Sentiment Score per Hour
- Reddit political subreddits experienced a sizable increase in activity during the election results
- Subreddits differed in their reactions to the news along idealogical lines, with pro-Trump subreddits having higher positive sentiment than pro-Clinton subreddits
What could be the next steps for this type of analysis?
- Can we use these patterns to classify the readership of the comments sections of newspapers as left- or right-leaning?
- Can we apply these time-series sentiment analyses to other events, such as sporting events (which also includes two ‘teams’)?
- Can we use sentiment analysis to evaluate the long-term health of communities, such as subreddits dedicated to eventually-losing candidates, like Bernie Sanders?