System Simulation Parameter Setting Table.

The breakthroughs in communication technologies, such as 5G, have significantly accelerated the popularity of high-traffic consumption entertainment activities, including short video live streaming and real-time broadcasting, making them one of the most prevalent social interaction methods today. It is the high activity level of such online engagements that has given rise to diversified online marketing business models, opening up new channels and opportunities for interactions between brands and consumers. This study focuses on the emerging “influencer marketing” strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between “brands” and “influencers” and establish a game-theoretic mechanism between them. During the construction of the influencer network, a novel concept—tunable clustering of influencers’ followers—is specifically introduced, followed by an analysis of how micro-level decision-making factors (from brands and influencers) and network structures influence the evolutionary mechanisms of macro-level cooperative emergence. This study focuses on the emerging “influencer marketing” strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between “brands” and “influencers”, establishing a game-theoretic mechanism between them and analyzing how micro-level decision-making factors (from brands and influencers) influence the evolutionary mechanisms of macro-level cooperative emergence. Specifically, during the construction of the influencer network, the network structural metric—tunable clustering—is integrated with the practical scenario of uneven follower distribution among influencers, thereby investigating the impact of influencer network clustering intensity on the system’s evolutionary dynamics. The research findings reveal that:(1) Influencer marketing represents a win-win cooperative model. (2) Brands’ decision-making outcomes are significantly affected by profit margins, additional costs, and commission rates. (3) Creative incentives and tunable clustering predominantly shape influencers’ decision-making behaviors. (4) Product lifecycles and platform extraction rate impact decisions of both parties, with brands exhibiting higher sensitivity to environmental changes. Followers’ trust levels in influencers have minimal influence on either party’s decisions. Finally, applying reasonable values derived from parameter experiments to the influencer marketing model in the cosmetics industry demonstrates that this approach effectively enhances mutual benefits and stabilizes the overall business environment.