Evolution and governance of online public opinion during COVID-19: a hybrid approach using communication visualization, SIR modeling, and simulation validation - Ren, Lin; Zhang, Jiehua; Su, Zhongyue; Lai, Fujun; Xiong, Deping (Frontiers in Physics, 2024)
The study proposes a two-stage SIR model based on the information waterfall theory to analyse the mechanism of public opinion dissemination and governance strategies in public health events. The principal nodes of public opinion are identified through Gephi visual analysis, and the precision and applicability of the model are verified by combining the model simulation with a simulation of the dynamic changes in the propagation of public opinion. It is demonstrated that the pivotal information nodes have a substantial detonation effect on the propagation of public opinion, whereas the ordinary nodes contribute to the natural calming of public opinion through their robust spontaneous recovery ability, thereby playing an instrumental role in regulating the diffusion of public opinion. The simulation analysis also identifies the optimal time for the government to intervene in the initial and peak periods of public opinion. Based on this, the study proposes recommendations to strengthen the management of key nodes, enhance public information literacy, optimise policy implementation, and use simulation to assist in public opinion management. These recommendations provide theoretical and practical references for public opinion management in public health events.