Tripartite Evolutionary Game Analysis of Online Rumor Governance in Major Emergencies: A Synergistic Governance Perspective

The governance of online rumors during major emergencies is essential for maintaining social stability and ensuring a healthy cyberspace. This study develops a tripartite evolutionary game model involving local governments, online media, and netizens by incorporating a central government punishment mechanism. The model systematically analyzes the strategic choices and dynamic evolutionary trajectories of these governance entities. Using replicator dynamics equations and stability analysis, we investigate how exogenous variables influence their behavioral strategies. The results reveal that the central punishment mechanism significantly increases the likelihood of positive responses from both online media and local governments. Moreover, stricter penalties imposed by local governments directly suppress netizens’ intention to spread rumors. Interestingly, while a higher rumor propagation rate reduces netizens’ tendency to disseminate rumors, it simultaneously prompts online media and local governments to intensify their intervention efforts. These findings highlight the adaptive strategic adjustments among governance entities and provide theoretical insights for optimizing collaborative rumor governance during emergencies.