An attention economy model of co-evolution between content quality and audience selectivity
Human attention has become a scarce and strategically contested resource in digital environments. Content providers increasingly engage in excessive competition for visibility, often prioritizing attention-grabbing tactics over substantive quality. Despite extensive empirical evidence, however, there is a lack of theoretical models that explain the fundamental dynamics of the attention economy. Here, we develop a minimal mathematical framework to explain how content quality and audience attention coevolve under limited attention capacity. Using an evolutionary game approach, we model strategic feedback between providers, who decide how much effort to invest in production, and consumers, who choose whether to search selectively for high-quality content or to engage passively. Analytical and numerical results reveal three characteristic regimes of content dynamics: collapse, boundary, and coexistence. The transitions between these regimes depend on how effectively audiences can distinguish content quality. When audience discriminability is weak, both selective attention and high-quality production vanish, leading to informational collapse. When discriminability is sufficient and incentives are well aligned, high- and low-quality content dynamically coexist through feedback between audience selectivity and providers' effort. These findings identify two key conditions for sustaining a healthy information ecosystem: adequate discriminability among audiences and sufficient incentives for high-effort creation. The model provides a theoretical foundation for understanding how institutional and platform designs can prevent the degradation of content quality in the attention economy.