Who has dominated information spreading on social media during the early stage of COVID-19 pandemic in China? A temporal network analysis

Abstract

In times of crisis, social media emerges as a pivotal channel for government-public communication. This study delves into the dynamics of a temporal weighted network on Weibo, analyzing 39,567,227 reposted data points related to the COVID-19 pandemic, specifically during its critical early stage. We examine the information dissemination roles of eight distinct user types: state-run news media, non-state-run news media, influential we media, normal we media, celebrities, organizations, governmental departments, and normal users. This is achieved through the application of three centrality metrics: temporal weighted degree centrality (TWDC), temporal weighted closeness centrality (TWCC), and temporal weighted betweenness centrality (TWBC), focusing on three cases (Top 10, Top 20, and Top 50) based on ranking results. Our findings reveal that while state-run news media were prolific in information publishing, their roles as central and mediator agents in information spreading were comparatively weaker than those of non-state-run news media and we media, especially influential we media. This pattern underscores potential risks in false information propagation and highlights gaps in the government's information dissemination strategy during the early stages of the pandemic. The study offers targeted theoretical and practical implications, suggesting how governments might more effectively leverage social media for crisis communication, thereby enhancing their role in combating misinformation and guiding public perception. These insights are crucial for framing more responsive and adaptive communication strategies in the initial phases of a crisis, providing a global blueprint for effective information management in public health emergencies.