Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates
This work addresses online harassment of political figures on social media, providing insights for platform moderation, but it is incremental as it builds on existing research in social media analysis.
The study analyzed Twitter users who engage in adversarial interactions with political candidates, finding that such users have decreased social graph centrality and increased attention to opposing-party candidates, with highly adversarial users showing fewer supportive interactions and more negativity in profiles.
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.