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University of Michigan School of Information


DS/CSS Seminar Series: Ashwin Rajadesingan

02/27/2020, 12:00 pm - 01:00 pm
North Quad 2255

Exploring strategies to depolarize online political conversations


Everyday casual political conversations, through which individuals construct their identities, recognize others’ perspectives and form considered opinions are central to a vibrant deliberative democracy. Such interactions online are especially known to foster political mobilization and participation. However, the quality of these online conversations is declining; now roughly half of social media users finding online political discussions to be less civil, less respectful and more angry than offline conversations. A major contributing factor in the prevalence of low quality political discussions is the noted recent increase in affective polarization, a tendency of partisans to view opposing partisans negatively and co-partisans positively. In this talk, drawing on social science theories, I detail two ongoing approaches to depolarize online political discussions: Can priming a superordinate identity such as the American national identity improve conversation quality between partisans? Does individuating users to see beyond partisan identities or highlighting shared social identities improve political discussions online?

Speaker bio: 

Ashwin Rajadesingan

Ashwin Rajadesingan is a 3rd year PhD student at the University of Michigan’s School of Information. His research is broadly on computational social science and social computing aimed at building better online communities. Currently, he focuses on making conversations in online communities more deliberative and insightful. Drawing from social psychology and political science theories, he designs studies, both observational and experimental, to inform building online spaces that can facilitate quality cross-cutting political interactions. He's advised by Ceren Budak and Paul Resnick.

Before starting his PhD, he worked at Doximity, a social network for medical professionals, as a data scientist for a few years. He has a master's degree in computer science from Arizona State University, where he worked with Huan Liu on detecting sarcasm. Before that, he completed his bachelor's degree in computer science from VIT University, India, during which time he worked with Ponnurangam Kumaraguru at IIIT Delhi on detecting phishing attacks.