Tripartite Evolutionary Game Analysis of Governance for Magic Performances Involving Animals in Digital Media: Interactions among Magicians, Exposers, and Content Platforms

Digital platforms have transformed magic performances involving animals from largely stage-bound practices into recordable, distributable, and publicly contested content. This transformation creates interdependent tensions among animal-welfare oversight, the protection of magic secrets, short-term traffic incentives, creator interests, and the long-term governance objectives of content platforms. This study develops a tripartite evolutionary game model involving magicians, content publishers who expose magic-related information (hereafter, exposers), and content platforms. Magicians choose between animal-friendly innovative magic and traditional live-animal magic; exposers choose between public exposure and compliance with professional and platform norms; and platforms choose between active content governance and traffic-oriented recommendation. Replicator dynamics and Jacobian-based stability analysis are used to characterize the evolutionary equilibria, followed by numerical simulations under different initial strategy probabilities, platform-governance benefits, penalty intensities, and exposure-related losses. The results show that the animal-friendly governance equilibrium is asymptotically stable when the payoff from public exposure is lower than the combined non-platform constraint, long-term compliance benefit, and platform penalty, and when the platform’s governance benefit exceeds its governance cost plus the baseline recommendation benefit available under non-governance. Numerical analysis further shows that platform-governance benefits can change the evolutionary destination, whereas penalty intensity primarily affects convergence speed and exposure-related losses mainly influence the transient behavior of magicians. These findings connect animal-welfare assessment, professional norms in magic, and platform governance within a unified incentive-based framework and suggest that sustainable governance depends more on reshaping long-term payoff structures than on punishment alone.