Quarterly Journal of Political Science > Vol 16 > Issue 1

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

Alexandra A. Siegel, University of Colorado Boulder and New York University, USA, alexandra.siegel@colorado.edu Evgenii Nikitin, New York University, USA, e.nikitin@nyu.edu Pablo Barberá, New York University and University of Southern California, USA, pbarbera@usc.edu Joanna Sterling, New York University and Princeton University, USA, joanna.sterling@princeton.edu Bethany Pullen, New York University, USA, bethanyjpullen@gmail.com Richard Bonneau, New York University, USA, rbonneau@flatironinstitute.org Jonathan Nagler, New York University, USA, jonathan.nagler@nyu.edu Joshua A. Tucker, New York University, USA, joshua.tucker@nyu.edu
 
Suggested Citation
Alexandra A. Siegel, Evgenii Nikitin, Pablo Barberá, Joanna Sterling, Bethany Pullen, Richard Bonneau, Jonathan Nagler and Joshua A. Tucker (2021), "Trumping Hate on Twitter? Online Hate Speech in the 2016 U.S. Election Campaign and its Aftermath", Quarterly Journal of Political Science: Vol. 16: No. 1, pp 71-104. http://dx.doi.org/10.1561/100.00019045

Publication Date: 11 Jan 2021
© 2021 A. A. Siegel et al.
 
Subjects
Elections: Campaigns,  Campaigns,  Presidential politics
 
Keywords
Hate speechsocial mediaDonald TrumpTwittertext-as-data
 

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In this article:
Motivation and Expectations 
Data and Measurement 
Empirical Strategy and Dictionary-Based Results 
Robustness Check: Reference-Text Based Analysis 
Conclusions and Steps for Future Research 
References 

Abstract

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.

DOI:10.1561/100.00019045