Social Dynamics and Mobilization Potential of Online Election Narratives

Abstract

The fragmentation of social media challenges how we might efficiently and effectively identify, understand, and counter harmful content. Prior work establishes frameworks for measuring problematic narratives, evaluating harms, and leveraging interdisciplinary theories and findings to design mitigating solutions. However, there is little understanding of these phenomena outside of mainstream platforms. This is particularly concerning given that alt-tech users have been observed to include insurrectionists, active shooters, and other extremists – often driven from mainstream platforms due to deplatforming and content moderation . Our work aims to characterize online narratives across alt-tech platforms. In particular, we highlight how rumoring and conspiracy theory narratives in the context of the 2022 U.S. elections impact social dynamics and inspire collective action. We gather a unique dataset of over 7,000 social media posts from Gab, Gettr, Parler, and Truth Social from which we derive prevalent narratives using natural language processing techniques. We then examine how the platform, affect, and engagement differ across context through the lens of narrative, social identity, and mobilization potential using mixed methods. Findings from our analyses show variation between how narratives support social identity conceptions of power and mobilization potential.