2016 Election


  • Journal Article

    The Times They Are Rarely A-Changin': Circadian Regularities in Social Media Use

    Journal of Quantitative Description: Digital Media, 2021

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    This paper uses geolocated Twitter histories from approximately 25,000 individuals in 6 different time zones and 3 different countries to construct a proper time-zone dependent hourly baseline for social media activity studies.  We establish that, across multiple regions and time periods, interaction with social media is strongly conditioned by traditional bio-rhythmic or “Circadian” patterns, and that in the United States, this pattern is itself further conditioned by the ideological bent of the user. Using a time series of these histories around the 2016 U.S. Presidential election, we show that external events of great significance can disrupt traditional social media activity patterns, and that this disruption can be significant (in some cases doubling the amplitude and shifting the phase of activity up to an hour). We find that the disruption of use patterns can last an extended period of time, and in many cases, aspects of this disruption would not be detected without a circadian baseline.

    Area of Study

    Date Posted

    Apr 26, 2021

  • Journal Article

    Trumping Hate on Twitter? Online Hate Speech in the 2016 U.S. Election Campaign and its Aftermath.

    Quarterly Journal of Political Science, 2021

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    To what extent did online hate speech and white nationalist rhetoric on Twitter increase over the course of Donald Trump's 2016 presidential election campaign and its immediate aftermath? The prevailing narrative suggests that Trump's political rise — and his unexpected victory — lent legitimacy to and popularized bigoted rhetoric that was once relegated to the dark corners of the Internet. However, our analysis of over 750 million tweets related to the election, in addition to almost 400 million tweets from a random sample of American Twitter users, provides systematic evidence that hate speech did not increase on Twitter over this period. Using both machine-learning-augmented dictionary-based methods and a novel classification approach leveraging data from Reddit communities associated with the alt-right movement, we observe no persistent increase in hate speech or white nationalist language either over the course of the campaign or in the six months following Trump's election. While key campaign events and policy announcements produced brief spikes in hateful language, these bursts quickly dissipated. Overall we find no empirical support for the proposition that Trump's divisive campaign or election increased hate speech on Twitter.

    Date Posted

    Jan 11, 2021

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