An attention economy model of co-evolution between content quality and audience selectivity

2026-02-06

AI Summary

This study addresses the degradation of content quality in attention-scarce environments, where producers often sacrifice quality to compete for user attention, a dynamic lacking a formal theoretical framework. The authors propose a minimal mathematical model grounded in evolutionary game theory, integrating differential equation analysis and numerical simulations to capture the strategic feedback between producers’ effort investment and audiences’ selective attention. The work reveals three canonical coevolutionary dynamics—collapse, boundary, and coexistence—between content quality and audience selectivity. Crucially, it identifies two key conditions for sustaining a healthy information ecosystem: sufficient audience discernment and well-designed platform incentive mechanisms. These findings provide a theoretical foundation for designing platform policies that foster the emergence of high-quality content.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization

Abstract

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.

Problem

• attention economy
• content quality
• audience selectivity
• information ecosystem
• coevolution

Innovation

• attention economy
• coevolution
• evolutionary game theory
• content quality
• audience selectivity