Deciphering the 2016 U.S. Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists

By Yu Wang, Yuncheng Li, Jiebo Luo. 2016

70 citations recorded by the source corpus.

In this paper, we study follower demographics of Donald Trump and Hillary Clinton, the two leading candidates in the 2016 U.S. presidential race. We build a unique dataset US2016, which includes the number of followers for each candidate from September 17, 2015 to December 22, 2015. US2016 also includes the geographical location of these followers, the number of their own followers and, very importantly, the profile image of each follower. We use individuals' number of followers and profile images to analyze four dimensions of follower demographics: social status, gender, race and age. Our study shows that in terms of social influence, the Trumpists are more polarized than the Clintonists: they tend to have either a lot of influence or little influence. We also find that compared with the Clintonists, the Trumpists are more likely to be either very young or very old. Our study finds no gender affinity effect for Clinton in the Twitter sphere, but we do find that the Clintonists are more racially diverse.

Subfields: Communication, Sociology and Political Science

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “…they are central to a research study, in others their use is more subtle or peripheral: e.g., a study analyzing public opinion or popularity across demographics may infer those demographics using pre-trained models for facial recognition (e.g., Wang Y. et al., 2016b; Chakraborty et al., 2017).”
How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers (2017, background): “In particular, researchers have attempted to capture demographic differences (e.g. gender and race) between Trump followers and Clinton followers by examining exclusively the proﬁle images [35, 33].”
Protest Activity Detection and Perceived Violence Estimation from Social Media Images (2017, unknown): “using profile photographs of Twitter users [46].”
Disinformation and social bot operations in the run up to the 2017 French presidential election (2017, unknown): “…the United States (Bessi & Ferrara, 2016; Kollanyi, et al., 2016; Shorey & Howard, 2016; Wolley, 2016; Wolley & Howard, 2016; Marwick & Lewis, 2017; Wang, et al., 2017), and all over the world, including in South America (Forelle, et al., 2015; Suárez-Serrato, et al., 2016), the U.K. (Howard &…”