Conference Agenda

Instant Messaging (IM) services have become crucial for Social Movement Organizations (SMOs), enabling activist coordination, information distribution, and mobilization for protest events. While previous research highlights the reduced importance of local dependencies due to digital communication, many left-wing SMOs continue to rely on decentralized local action as a core organizational principle. Antifa exemplifies this dual structure, leveraging Internet Communication Technologies (ICTs) and instant messaging to combine localized direct action with an (inter)national activist network. Existing case studies suggest that local demonstrations remain vital for antifascist groups in European cities. However, the role of spatial proximity in information diffusion and mobilization within these networks remains understudied. This study examines how spatial proximity influences information dissemination among German antifascist groups and channels on Telegram over time, considering their strong reliance on IM services and localized offline protest behavior. Using transportation time by car and bus as a proxy for spatial proximity, we analyze event-driven communication patterns. We extract topics from (forwarded) messages and mentions in German antifascist Telegram groups and channels linked to direct actions, constructing a longitudinal network dataset to track information diffusion over time. Stochastic Actor-Oriented Models (SAOMs) assess how transportation time affects information diffusion dynamics. Additionally, we test the role of ideological and topical similarity in shaping dissemination patterns. By integrating natural language processing and network analysis, this study provides empirical insights into the structuring impact of spatial proximity on mobilization in a fragmented yet interconnected digital antifascist landscape.