University of Illinois - Chicago
User Engagement Dynamics: The Impact of Platform Design and Generative AI
Abstract
dc:descriptionThis dissertation investigates how platform design choices and AI integration reshape user engagement dynamics on digital platforms. As platforms redesign interfaces and deploy AI-enabled features at scale, understanding how specific design choices influence feedback loops, cognitive load, and content discovery has become critical for designing sustainable digital ecosystems. Through three empirical studies using large-scale behavioral data, this dissertation examines the consequences of two distinct platform mechanisms: restricting negative feedback visibility and embedding AI-driven features into platform interactions. The first study analyzes YouTube's 2021 decision to hide public dislike counts. Using a difference-in-differences approach, the findings reveal that this intervention significantly reduced viewer engagement and video popularity. The negative effect was disproportionately concentrated among smaller channels, which historically relied on dislike signals as quality indicators, suggesting that restricting feedback visibility can undermine the feedback loops that sustain creator motivation and content quality. The second study examines Bilibili's introduction of AI-generated video summaries. Drawing on cognitive load theory, the results show that these summaries increased user engagement by lowering cognitive barriers for long-form, utilitarian content. The effect was especially pronounced for informationally dense videos, highlighting how AI-driven content synthesis can facilitate discovery and deepen consumption when aligned with user needs. The third study explores the deployment of Grok, a socially embedded AI agent (SEA), on X.com. The findings demonstrate that Grok revitalized long-tail discussions by lowering discovery barriers and broadening participant diversity, particularly in niche topic areas that previously struggled to sustain engagement. Collectively, these findings advance our theoretical understanding of how platform design and AI integration interact with human cognition and social behavior. They also offer practical guidance for platform designers seeking to balance engagement, inclusivity, and long-term viability in digital ecosystems.
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
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- Ahreum Kim (407075)
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
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- In Copyright
- Open Access after 2028-05-01
Identifiers
dc:identifier.*- DOI dc:identifier
- https://doi.org/10.25417/uic.32995154.v1
- OAI identifier oai:identifier
- oai:figshare.com:article/32995154