The COVID‐19–Social Identity–Digital Media Nexus in India: Polarization and Blame

Arabaghatta Basavaraj, Kiran; Saikia, Pahi; Varughese, Anil; Semetko, Holli A.; Kumar, Anup

Drawing on social identity theory and research on digital media and polarization, this study uses a quasi‐experimental design with a random sample (n = 3304) to provide causal evidence on perceptions of who is to blame for the initial spread of COVID‐19 in India. According blame to three different social and political entities—Tablighi Jamaat (a Muslim group), the Modi government, and migrant workers (a heterogeneous group)—are the dependent variables in three OLS regression models testing the effect of the no‐blame treatment, controlling for Facebook use, social identity (religion), vote in the 2019 national election, and other demographics. Results show respondents in the treatment group were more likely to allay blame, affective polarization (dislike for outgroup members) was social identity based, not partisan based, and Facebook/Instagram use was not significant. Congress and United Progressive Alliance voters in 2019 were less likely to blame the Modi government for the initial spread. Unlike extant research in western contexts, affective and political polarization appear to be distinct concepts in India where social identity complexity is important. This study of the first wave informs perceptions of blame in future waves, which are discussed in conclusion along with questions for future research.