Designing AI-Infused Interactive Systems for Online Communities: A Systematic Literature Review

2025-09-27

AI Summary

A systematic review of AI-augmented online community interaction systems is currently lacking. This study conducts a systematic literature review of 77 relevant works and proposes, for the first time, a classification framework grounded in four core community participation dimensions: contribution, consumption, mediation, and governance. Through qualitative thematic analysis and cross-study comparison, we identify prevalent AI functionality patterns—including content recommendation, collaborative support, and governance assistance—as well as associated evaluation strategies. We distill six foundational design principles that jointly optimize user engagement efficacy and sustainable community governance. This work bridges a critical theoretical gap at the intersection of AI interaction design and community mechanism design, offering transferable design guidelines and empirically grounded insights for next-generation community-oriented intelligent agent systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Humans and AI: Interaction Techniques and Devices
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

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.

Problem

• Synthesizing AI system research for online communities
• Analyzing design and evaluation patterns systematically
• Identifying challenges in community participation dimensions

Innovation

• Systematic review of 77 AI-infused system studies
• Analyzes systems through challenges, design, and evaluation
• Organizes findings around community participation aspects