Coupled dynamics of information propagation and emotion influence: Emerging emotion clusters for public health emergency messages on the Chinese Sina Microblog

Abstract

A major distinction between the COVID-19 pandemic and previous pandemics is the significant role of social media platforms in shaping public adherence to non-pharmaceutical interventions and vaccine acceptance. The information propagation and individual emotion communication relevant to public health messages have been promoted in the Chinese Sina Microblog, one of the most popular social platforms in China, through two major interaction mechanisms, “commenting” and “forwarding”. Here, we develop a hybrid system of macro information propagation dynamics Susceptible-Commenting-Forwarding-Immune model coupled with the micro emotion influence dynamics Hegselmann-Krause model, termed HK-SCFI coupled system, and reveal the mechanisms of individual emotion infection using the commenting and forwarding data (including time point and content) publicly available on public opinion events in the Chinese Sina Microblog. We demonstrate how our data-driven and model-informed analysis can provide quantitative insights into the co-evolution mechanism of individual emotion during information propagation, describe the emergency of emotion clusters, and predict individual emotion evolution trends. Our study shows that multiple interactive mechanisms can facilitate the propagation of public messages and shape public sentiment through online social networks. Our modeling framework can potentially be a tool for designing effective propagation strategies during public health emergencies.