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

Area of Science:

• Information Science
• Sociology
• Complex Systems

Background:

• Online public opinion systems are crucial during human-made disasters.
• Understanding information diffusion and uncertainty is vital for effective crisis management.

Purpose of the Study:

• To investigate information diffusion and uncertainty dynamics in online public opinion during human-made disasters.
• To propose and validate a modified SIR model incorporating psychological and herd behavior.

Main Methods:

• Developed a variant of the SIR model with psychological involvement and herd behavior.
• Conducted theoretical analysis to determine equilibrium points and propagation thresholds.
• Performed simulations to validate findings and assess parameter sensitivity.
• Validated the model with an empirical case study.

Main Results:

• Transmission rate, immunity rate, and herd behavior coefficient significantly influence public opinion dynamics.
• Controlling contact rates, herd behavior, and psychological involvement can suppress opinion diffusion.
• Herd behavior and psychological involvement have a greater impact than contact rate on opinion spreaders.
• Reducing herd behavior increases system uncertainty.

Conclusions:

• Mitigating emotional resonance and herd effects is an effective strategy for public opinion governance in man-made disasters.
• Reducing herd behavior, while effective, introduces greater system uncertainty.
• Findings offer practical guidance for governments in developing public opinion management strategies and transforming systems from disorder to order.