US President Donald Trump is perhaps the most powerful man on Twitter in terms of both his office and his ability to impact world events through his tweets. The way he uses the platform is unusual for someone in his position and is divisive among US citizens. Some tweets are posted by staff while others are posted by Trump himself, and in the time period of our dataset, the platform used to post distinguishes the author. We use this data to study the behavioral characteristics of the tweet sources and the public reaction to this content. Trump tweets tended to be more focused on himself or and other people, rather than the audience, and are more negative, angry, and anxious than staffers' tweets. Liberals and conservatives alike found some of the tweets inappropriate for someone in Trump's position to be posting, and the majority of inappropriate tweets came from Trump himself. The language characteristics are so distinctive that they may be used in a predictive model to correctly classify a tweet's author with 87% accuracy. Our predictive model will low for authorship determination, even when platform information is not informative, and our analysis suggests directions for future research on the rise of populist candidates and how they communicate on social media.
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