SIGecom Winter Meeting 2025 Highlights

The first invited talk of the session, by Haifeng Xu from the University of Chicago, highlighted a new research agenda: studying the wide range of problems in online content ecosystems through the formalisms of computational economics. Online content recommendation engines—core to platforms like YouTube, Instagram, and TikTok—serve personalized content to billions of users daily. The classic model considers both the users and the content library to be static, with the recommendation engine responsible for generating a mapping between the two. Xu's talk envisions a richer model that incorporates the incentives of content creators (e.g., YouTube rewarding videos based on length and views), the myopic and dynamic behavior of consumers, and the increasingly prominent role of AI in both generating content and being trained on it. This is a rich, dynamic multi-agent environment and the remainder of the talk considers two distinct directions within this framework:

(1) Diagnosing and optimizing existing content ecosystems

(2) How AI-generated content can transform future content ecosystems