Designing AI-Infused Interactive Systems for Online Communities: A Systematic Literature Review
This work synthesizes existing research to guide the design of AI systems for online communities, addressing a gap in comprehensive synthesis, but it is incremental as it reviews rather than proposes new methods.
The paper conducted a systematic literature review of 77 studies on AI-infused interactive systems for online communities, analyzing them based on challenges, design functionalities, and evaluation strategies to identify patterns and future research opportunities.
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.