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Computer Science > Social and Information Networks

arXiv:1605.09473 (cs)
[Submitted on 31 May 2016]

Title:Will Sanders Supporters Jump Ship for Trump? Fine-grained Analysis of Twitter Followers

Authors:Yu Wang, Yang Feng, Xiyang Zhang, Richard Niemi, Jiebo Luo
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Abstract:In this paper, we study the likelihood of Bernie Sanders supporters voting for Donald Trump instead of Hillary Clinton. Building from a unique time-series dataset of the three candidates' Twitter followers, which we make public here, we first study the proportion of Sanders followers who simultaneously follow Trump (but not Clinton) and how this evolves over time. Then we train a convolutional neural network to classify the gender of Sanders followers, and study whether men are more likely to jump ship for Trump than women. Our study shows that between March and May an increasing proportion of Sanders followers are following Trump (but not Clinton). The proportion of Sanders followers who follow Clinton but not Trump has actually decreased. Equally important, our study suggests that the jumping ship behavior will be affected by gender and that men are more likely to switch to Trump than women.
Comments: Election-series, 4 pages, 6 figures, under review for CIKM 2016. arXiv admin note: substantial text overlap with arXiv:1605.05401
Subjects: Social and Information Networks (cs.SI)
Cite as: arXiv:1605.09473 [cs.SI]
  (or arXiv:1605.09473v1 [cs.SI] for this version)
  https://doi.org/10.48550/arXiv.1605.09473

Submission history

From: Yu Wang [view email]
[v1] Tue, 31 May 2016 02:51:15 UTC (685 KB)
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Yang Feng
Xiyang Zhang
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