Cyberbalkanization Without Monotonic Polarization: Temporal Dynamics and User Heterogeneity in Online Debates on Traditional Chinese Medicine

This paper examines the polarization and cyberbalkanization of opinions within a Traditional Chinese Medicine (TCM) community on Zhihu, a prominent Chinese social question-answering platform. The study explores the impact of online interactions on opinion dynamics during the COVID-19 pandemic. Utilizing a hybrid content and network analysis approach, the research identifies distinct subcommunities within the TCM debate and analyzes the influence of opinion leaders and user participation. The study finds a high level of cyberbalkanization, with users forming segregated communities based on their views towards TCM. However, contrary to expectations, the overall polarization levels do not increase monotonically over time, despite fluctuations during peak discussion periods. Further analysis reveals that the influx of moderate views from low-engagement users during heated debates counterbalances the extreme rhetoric of high-engagement partisan users. The longitudinal patterns suggest a potential convergence of views between the entrenched and peripheral users over time. These findings highlight the nuanced interplay between cyberbalkanization and polarization within online communities, challenging assumptions of an inevitable polarizing effect. The study underscores the importance of considering user heterogeneity and temporal dynamics when examining opinion polarization in digital spaces, offering insights into the complex forces shaping public discourse in the contemporary media environment.