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Characteristic Subject Matter and Logical Framing: Driving Deep and Lasting Online Communication with Notable Public Impact and Structural Polarization

China
Social Media
Communication
Mixed Methods
Activism
Big Data
Xin Gao
University of Copenhagen
Xin Gao
University of Copenhagen

Abstract

This exploratory study examines how different topics influence information diffusion and polarization in online activism, using the Red-Yellow-Blue kindergarten child abuse scandal on the Chinese social media Weibo as a case study. We investigate networked patterns of diffusion and polarization, focusing on the roles of various actors and potential outcomes of these message flows. Using topic modeling, content analysis, and social network analysis, we initially identify five topic categories, each requiring different levels of analytical thinking. We assess spreading patterns through network depth, virality, actor centrality, and flow network variables. The study further employs crisp-set Qualitative Comparative Analysis (csQCA) to explore conditions leading to network variations and polarization. Our findings show that topics involving celebrity influencers have greater depth and virality in diffusion networks. These celebrities effectively convey attitudes and emotions, leveraging their social status and public trust. Posts involving them demonstrate a viral spreading pattern across network steps. Furthermore, we identify four main actor types (official government, media, individual influencers, uncertified users) and their roles in the contagion process, including as "emotion initiators," disseminators, and intermediaries. We also assess polarization in structural, sentiment, and content dimensions. Topics related to rumors showed higher structural polarization with limited, ephemeral diffusion. Conversely, topics with depressive emotions, despite high analytical levels, led to echo chambers and content and sentiment polarization. This research addresses the impact of social media on public discourse and online activism, clarifying the relationships within flow network structures and the effects of topic types on misinformation and polarization. Our study contributes to understanding online discussions, echo chambers, misinformation, and internet governance within Chinese social platforms.