Designing AI-Infused Interactive Systems for Online Communities: A Systematic Literature Review
September 27, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Yuanhao Zhang, Xiaoyu Wang, Jiaxiong Hu, Ziqi Pan, Zhenhui Peng, Xiaojuan Ma
arXiv ID
2509.23309
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
AI-infused systems have demonstrated remarkable capabilities in addressing diverse human needs within online communities. Their widespread adoption has shaped user experiences and community dynamics at scale. However, designing such systems requires a clear understanding of user needs, careful design decisions, and robust evaluation. While research on AI-infused systems for online communities has flourished in recent years, a comprehensive synthesis of this space remains absent. In this work, we present a systematic review of 77 studies, analyzing the systems they propose through three lenses: the challenges they aim to address, their design functionalities, and the evaluation strategies employed. The first two dimensions are organized around four core aspects of community participation: contribution, consumption, mediation, and moderation. Our analysis identifies common design and evaluation patterns, distills key design considerations, and highlights opportunities for future research on AI-infused systems in online communities.
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