Governing digital misinformation: A computational analysis of platform intervention using a three-party evolutionary game model

The proliferation of misinformation on short video platforms poses a significant challenge to digital governance and public trust. While platforms are central actors, their strategic role in rumor governance remains underexplored. This study introduces a tripartite evolutionary game model that incorporates the platform as a bounded rational strategic actor alongside rumor spreaders and information clarifiers, and combines this model with the extended SICR (Susceptible-Rumor spreader-Clarifier-Recovered) information diffusion framework, where game strategies and payoffs are defined based on user roles. This combined framework allows us to analyze the strategic interactions among these three agents. Numerical simulations identify key evolutionary stable states and reveal that increasing the probability and perceived benefits of platform intervention can effectively steer the system towards an ideal equilibrium where platforms strictly supervise, and clarifiers actively debunk rumors. A case study of the "Hengshan Bus" incident supports the model's applicability, demonstrating that proactive platform intervention accelerates the dissemination of corrective information. Our findings illustrate the important and strategically complex role of platforms in self-regulation, and provide insights for co-governance mechanism design on Chinese short-video platforms.