Evolutionary Game Analysis of AI-Generated Disinformation Governance on UGC Platforms Based on Prospect Theory

While Generative Artificial Intelligence technology empowers content production on user-generated content platforms, it also gives rise to novel risks of disinformation dissemination. The effective governance of these risks is critical to ensuring the cybersecurity of the online ecosystem and maintaining long-term social stability. To address the collaborative governance dilemma, this study constructs a tripartite “platform-user-government” evolutionary game model based on prospect theory. It explores the evolutionarily stable strategies and stability conditions of each actor, supplemented by numerical simulations and practical case validation. The results indicate that: (1) under specific conditions, the system can converge to an ideal equilibrium {active platform governance, engaged user participation, stringent government supervision}; (2) the government’s reward–penalty mechanisms can drive the system towards this ideal equilibrium; (3) users’ digital literacy is a key variable influencing the system’s evolutionary path; (4) both the risk preference coefficient (β) and loss aversion coefficient (λ) from prospect theory have a significant moderating effect on the system’s evolution. Finally, targeted recommendations are proposed for the three aforementioned stakeholders to accelerate the improvement of China’s collaborative governance of the content ecosystem.