Abstract

Amidst growing societal tensions, social media platforms become hubs of heated intergroup exchanges. According to social identity theory, group membership and the value we assign to it drive the expression of intergroup bias. Within the blooming scholarship on social and political polarization online, little attention has been paid to interreligious deliberations, despite the well-established relationship between religion and intergroup grievances. The present studies are designed to address the void in the scholarship of social identity and online religion by examining how religious identities, or the lack thereof, affect intergroup biases in the form of identity-specific topic preferences and topic-sentiment polarization. Drawing from social identity theory, five hypotheses were tested. The data for the study, a product of a natural experiment, are YouTube commentary sections featuring videos on two cases of interreligious debates between (1) Christian and Muslim or (2) Christian and atheist speakers. Using topic-sentiment analysis, a multistage method of topic modeling with latent semantic analysis and sentiment analysis, 24,179 comments, for the Christian–Muslim debates, and 52,607 comments, for the Christian–atheist debates, were analyzed. The results demonstrate normative content and identity-specific instances of topic-sentiment polarization. In terms of content, Christian–Muslim and Christian–atheist discussions are nearly completely preoccupied with theological or intellectual concepts. While interreligious polarization is robust in both debates, it appears more normative among Christians–Muslims and deeper among Christians–atheists, possibly indicating the higher stakes in the battle for moral authority. Interreligious debates on YouTube serve to uplift and defend the in-group and to delegitimize the outgroup in a broader battle for moral authority. Regardless of group affiliation, these debaters were concerned with ‘big picture’ questions of meaning and how best to address them. Stereotyping and cultural altercations appear mostly as a reaction to challenged identity characteristics, suggesting that issue-based social differences and cultural incompatibilities, often emphasized in self-report research, may be evoked as rationalizations of interreligious prejudice. Last, the successful application of topic-sentiment analysis lends support for the more systematic utilization of this method.

Highlights

  • Identity-work and its relationship with intergroup behavior have received extensive attention within the academic community

  • Social identity theory (SIT) argues that our social memberships are instrumental for the emergence of social identities and structure how we understand ourselves, what we believe, and how we interact with others who belong to the in-group or not (Brown 2000; Hogg et al 1995; Tajfel and Turner 1979)

  • The present study seeks to contribute to research related to social identity theory and online religion by examining howreligious identities contribute to online interreligious polarization

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Summary

Introduction

Identity-work and its relationship with intergroup behavior have received extensive attention within the academic community. Social identity theory (SIT) argues that our social memberships are instrumental for the emergence of social identities and structure how we understand ourselves, what we believe, and how we interact with others who belong to the in-group or not (Brown 2000; Hogg et al 1995; Tajfel and Turner 1979). Despite the extensive research in the context of SIT, the effect of religious membership as a social identity has been rather neglected (see Hogg et al 2010; Ysseldyk et al 2010). The present study seeks to contribute to research related to social identity theory and online religion by examining how (ir)religious identities contribute to online interreligious polarization. Provided a considerable lack of research on social identity in real-world interactions, this study takes a step forward by taking advantage of big data techniques and social media data

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