Engagement maximization

• 成果类型: Article
• 署名作者: Hebert, Benjamin; Zhong, Weijie
• 署名单位: Stanford University; University of Cambridge
• 刊物名称: THEORETICAL ECONOMICS
• ISSN/ISSBN: 1933-6837
• DOI: 10.3982/TE6567
• 发表日期: 2026
• 关键词: information

摘要

We investigate the management of information provision to maximize user engagement. A principal sequentially reveals signals to an agent who has a limited amount of information processing capacity and can choose to exit at any time. We identify a dilution strategy-sending rare but highly informative signals-that maximizes user engagement. The platform's engagement metric shapes the direction and magnitude of biases in provided information relative to a user-optimal benchmark. Even without intertemporal commitment, the platform replicates full-commitment revenue by inducing the user's belief to remain as uncertain as the prior until the rare, decisive signal arrives and induces stopping. We apply our results to two contexts: an ad-supported internet media platform and a teacher attempting to engage test-motivated students.