Social Identities in Twitter Issue Publics

In the digital age, platforms such as Twitter foster the emergence of fragmented issue-based communities online, intersecting with traditional media and broader national discourse. However, these digital public spheres often deviate from idealised concepts like those proposed by Habermas, showcasing uncivil discourse and participatory disparities. Recent research highlights a subset of hyperactive users on Twitter who monopolise discussions on contentious topics like abortion, perpetuating intolerance and incivility. Drawing on social psychological theories of social identity as discursive constructions, this study investigates how hyperactive uncivil and intolerant Twitter users present their identities. Analysing over 30,000 accounts, researchers scrutinise psycholinguistic patterns and emoji usage to answer two key questions: How do these hyperactive users describe their identities compared to non-hyperactive ones, and who are the verified, influencer accounts driving uncivil and intolerant discourse on abortion? The findings reveal distinct identity markers among hyperactive users compared to non-hyperactive ones. Notably, hyperactive uncivil and intolerant users display varied discursive identifications, often aligning with religious, partisan, and familial affiliations rather than directly addressing abortion-related identities like pro-choice or pro-life. Furthermore, there's a notable dominance of pro-life social identity in online discourse, potentially influencing online public opinion despite being a minority in national surveys. This research sheds light on the intricate relationship between discursive social identities and their hyperactive behaviours in Twitter issue publics. This study also contributes to our understanding of the key hyperactive actors in American Twitterspheres and beyond, driving incivility and intolerance in abortion discourse

Abortion · Biology · Political science · Pregnancy · Publics · Social media · Sociology · World Wide Web · Computer Science · Gender Studies · Hate Speech and Cyberbullying Detection · Social Media and Politics · Genetics