“His Tweets Speak for Themselves”

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Abstract

We used computational tools to explore president Donald Trump’s tweeting habits and some of the effects they have on his Twitter followers as well as a small sample of mainstream media. To gain a comprehensive picture of Trump’s tweeting habits as President of the United States, we have undertaken a study of Trump’s personal @realDonaldTrump Twitter account, focusing on his campaign, the transition period before his presidency, and his first two hundred days in office. We employed three state-of-the-art computational tools to analyze sentiment, emotions, and psycholinguistic features in Trump’s tweets as well as a manual semantic discourse analysis to decipher what it is about his communication methods that generates the highest responses and retweets. We found that during the first two hundred days of presidency, an accusative tone of discourse was most frequently used by @realDonaldTrump, and among a number of significant emotional patterns, we observed an intriguing correlation in that the more negative the overall message of a tweet, the more likely it is to be retweeted and favorited. We also find individual tweets to be discussed with high frequency in mainstream media and used data from the PTDC corpus (Political Twitter Discourse Corpus) consisting of 205,303 original tweets of all current US state governors, members of the US Senate, and members of Congress and found that Trump’s tweeting style is significantly different along a central dimension of language on Twitter. Our findings suggest that the general public on Twitter responds more actively to negative language, and in turn the language on Twitter employed by Trump is highly emotional with more-than-expected emotion-bearing expressions.