Text Analysis
SENTIMENT ANALYSIS
Exploring the emotions of the subreddits
Are people using r/JoeBiden less happy than people on r/DonaldTrump or is it the other way around? Are people engaging with a subreddit on Donald Trump more susceptible to mood swings?
We assigned a happiness score from 1-9 to all users based on the words of their comments. This made us able to compare the sentiments of the two user groups.
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FINDINGS
Sentiment box plot
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Most of the comments in both camps were discussing in a neutral manner.
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Comments on r/JoeBiden may be slightly more positive
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Emotions are more extreme in the comments on r/DonaldTrump
TEXT ANALYSIS
Language statistics
What are the users talking about? Which groups speaks about what?
Using natural language processing techniques such as
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term frequency distributions
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term frequency-term ratio
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term frequency-inverse document frequency
we were able to find the words that are specific to various user groups and visualize our findings in clouds of words.
We investigated different partitionings of users. We found some of the most informative partitionings to be
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r/DonaldTrump vs r/JoeBiden
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3 sentiment groups in both r/DonaldTrump and r/JoeBiden ranging from most negative over neutral to most positive.
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The comments from r/JoeBiden and r/DonaldTrump were first compiled into two documents with approximate 30,000 words in each.
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FINDINGS
Term frequency distribution
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Trump is the talk of the town: the term ”Trump” was the most used on both subreddits
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”Fuck” or ”thank”? The users on r/DonaldTrump say ”fuck” in about the same proportion as the users on r/JoeBiden say ”thank”.
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r/DonaldTrump talks more about black Americans than r/JoeBiden.
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r/JoeBiden users eagerly discuss about voting.
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Diving into the topics of discussion
Using NLTK (the Natural Langauge Toolkit) we also investigated the contexts of certain words to get a deeper understanding the words of the comments. In this way we learned that
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users on r/DonaldTrump think Democrats and Joe Biden are racist
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users on r/JoeBiden think Donald Trump and the people voting for him are racist.
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Visualizing sentiment group differences
Using an inner quartile range filter on the sentiment data we were able to partition both subreddits into a negative, neutral and positive comment segment and compile these comment segments into six documents.
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Negative Comments
Negative sentiment segment
r/DonaldTrump
Negative comments on r/DonaldTrump contains a lot of derogatory terms such as "bitch", ”monster”, "soyboys" and ”zuckfuck”.
Negative comments on r/JoeBiden are less personal: "terrorism", "fraud" and "violence” are prominent negative words but there are also personal derogatory terms such as ”turntables” and ”fuckers”.
r/JoeBiden
Neutral Comments
Neutral comments on both subreddits witness that the users engage in sober political discussions: Prominent words are ”people”, ”right”, ”vote”, ”republican” and ”democrat”.
Neutral sentiment segment
r/DonaldTrump
r/JoeBiden
Positive Comments
Positive sentiment segment
r/DonaldTrump
r/JoeBiden
​The positive r/DonaldTrump comments seem to mention "kim", "kimberly" and "klacik" quite a lot: This indicates there is a positive sentiment towards the Republican Kimberly Klacik on the subreddit
For the r/JoeBiden positive comment segment we see words such as "momma", "papa" and "heaven", ”god" and "believe". This points in the direction that family related issues and religious issues may appear more often in the r/JoeBiden comments in positive contexts
