An evolutionary game-Theoretic model and stability analysis of influencer compliance behavior from a perception-driven perspective
Year: 2025
Type: article
Abstract: Under the background of the government's reward and punishment mechanism, a dynamic game relationship is formed among internet influencers, regulatory institutions, and the Weibo platform, which affects the standardization process of the influencer economy. This study aims to systematically reveal the evolutionary logic and collaborative mechanism of the three parties in the process of normative governance. Based on evolutionary game theory, a tripartite game model is constructed to describe how differences in perception among multiple subjects influence strategic evolution. Through model derivation and numerical simulation, the paper analyzes the effects of key parameter changes on system stability, introducing perception coefficients (α, β, γ, λ) to depict the dynamic evolutionary paths of all parties. The study shows: (1) The system has three evolutionarily stable strategy combinations, namely: (influencers release harmful information, the government does not strictly regulate, and the platform does not supervise), (influencers release harmful information, the government does not strictly regulate, and the platform supervises), and (influencers release compliant information, the government does not strictly regulate, and the platform supervises). However, the only long-term effective stable point is when influencers release compliant information, the government does not implement strict regulation, and the Weibo platform supervises. (2) Factors such as enhanced perception of influencer income, reduced regulatory costs, and increased incentives for platforms can all improve the level of system standardization; before the release of information stabilizes at 1, increasing fines can enhance the intensity of government regulation; once stabilized, the regulation rate will decline and tend to zero. Increased subsidies for platform supervision can also increase the probability of government regulation; however, increasing subsidies for compliant influencers reduces the government's willingness to regulate, while increasing the platform's supervision probability. (3) Perception bias significantly affects the behavior of all parties, and the strategy evolution shows obvious threshold and nonlinear characteristics. The study reveals the key role of multi-agent collaborative governance mechanisms in guiding compliant behavior of influencers, and provides theoretical support for optimizing regulatory incentive policies and strengthening platform self-discipline.
Authors: Yujing Si, Wei Cao, Yi Yang
Institutions: Taiyuan University of Technology, Zhejiang University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,930
Award: G5390512059
OpenAlex ID: W4415680768