Research on the Emotional Evolution Mechanism of Online Public Opinion in Emergency Mass Events—Data Simulation Experiment Based on SEIR Model

ABSTRACT

The interaction between emergency mass incidents and online public opinion may lead to the rapid diffusion of public emotions and the escalation of online public opinion crises. Understanding how emotions evolve and diffuse in such contexts is therefore important for digital government, crisis communication and public opinion governance. Drawing on the SEIR framework, this study develops a modified SEIR‐based multi‐agent simulation model to examine the mechanisms underlying the evolution and diffusion of online emotions during emergency mass incidents. The model adapts the SEIR framework from biological contagion to emotional diffusion and incorporates government intervention, media‐related emotional sources and netizen participation. Using NetLogo, the study compares how changes in population size, netizen activity, emotional resistance, emotional sources and government intervention time are associated with different patterns in the speed, scale and duration of emotional diffusion under specified simulation conditions. The simulation results reveal distinct diffusion trajectories across different parameter settings, including non‐linear patterns associated with netizen activity and variations related to the timing of government intervention and emotional‐source conditions. The present analysis relies on scenario‐defined parameters and focuses on elucidating how emotional diffusion unfolds under varying conditions. Calibration and validation using platform‐level data from actual emergency events remain important directions for future research. The study contributes to the understanding of online emotional diffusion by integrating government, media and netizens within a common analytical framework and by identifying mechanisms and governance‐relevant propositions for subsequent empirical investigation.