A Public Opinion Propagation Model for Human-Made Disasters Considering Herd Behavior and Psychological Involvement

This study investigates the dynamics of information diffusion and uncertainty evolution in online public opinion systems under human-made disasters. A variant of the SIR model considering individual psychological involvement and group herd behavior is proposed. The theoretical analysis derives the propagation equilibrium points and the propagation threshold and further examines the stability of the system. The results indicate that the transmission rate, immunity rate, and herd behavior coefficient are key parameters influencing the dynamics of public opinion propagation. The simulation results validate the theoretical findings and provide a visualization of the sensitivity of the key parameters. Finally, an empirical case study is conducted to verify the effectiveness and applicability of the proposed model. The results indicate that controlling contact rate, reducing herd behavior, and lowering psychological involvement can effectively suppress opinion diffusion, with herd behavior and psychological involvement exerting a greater influence than contact rate on spreaders of the public opinion system. Consequently, mitigating public emotional resonance and herd effects constitutes an effective strategy for managing public opinion in human-made disasters, but reducing herd behavior makes the system relatively more uncertain compared with other scenarios. Finally, managerial implications for public opinion governance in human-made disasters are proposed. The findings enrich the theoretical system of information evolution modeling for complex social systems based on entropy and information theory, offer practical guidance for governments in developing scientific public opinion management strategies, and realize the transformation of public opinion systems from high-entropy disorder to low-entropy order.