ABSTRACT
This chapter takes Weibo as a case study to illustrate the dynamics of infodemic diffusion during the COVID-19 pandemic with a focus on the topological characteristics of the diffusion pattern, the profile information of participating users and the node types they represent, and the textual features of the information content. Using computational methods, we further analyze the relationship between social media user characteristics (e.g., location, verification status, the number of followers) and their varying levels of vulnerability to misinformation messages related to COVID-19. The findings show that the emergence of COVID-19 misinformation on Weibo is closely related to the severity of the epidemic in China. The dominant sources of misinformation tend to be unverified users. The spread range of the misinformation is smaller than that of true news, but the spread is deeper and has been persistent since the initial outbreaks. Most of the super-spreaders during the propagation process are the source post publishers; the most common grassroots users seem to be the most vulnerable group to COVID-19 misinformation.
