Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates

Описание: Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates
Yiqing Hua, Mor Naaman, Thomas Ristenpart

CHI '20: ACM CHI Conference on Human Factors in Computing Systems
Session: Political movement

Abstract
Social media provides a critical communication platform for political figures, but also makes them easy targets for harassment. In this paper, we characterize users who adversarially interact with political figures on Twitter using mixed-method techniques. The analysis is based on a dataset of 400 thousand users' 1.2 million replies to 756 candidates for the U.S. House of Representatives in the two months leading up to the 2018 midterm elections. We show that among moderately active users, adversarial activity is associated with decreased centrality in the social graph and increased attention to candidates from the opposing party. When compared to users who are similarly active, highly adversarial users tend to engage in fewer supportive interactions with their own party's candidates and express negativity in their user profiles. Our results can inform the design of platform moderation mechanisms to support political figures countering online harassment.

DOI:: https://doi.org/10.1145/3313831.3376548
WEB:: https://chi2020.acm.org/

Remote Presentations for the ACM CHI Conference on Human Factors in Computing Systems 2020.