The Decline of Online Knowledge Communities: Obstacles, Workarounds, and Sustainability
Ching Christie Pang, Xuetong Wang, Yuk Hang Tsui, Pan Hui

TL;DR
The paper examines how online knowledge communities adapt to the rise of Generative AI, highlighting challenges and opportunities for sustaining community engagement and trust amidst systemic shifts.
Contribution
It provides empirical insights into user attitudes and community dynamics in the face of AI-driven changes, proposing design strategies for resilience.
Findings
Users rely on AI for convenience but prefer OKC for complex questions.
Attitudes toward AI are polarized, with hopes and uncertainties.
Sociability and reciprocity are key to community resilience.
Abstract
Online knowledge communities (OKC) such as Stack Exchange, Reddit, and Zhihu have long functioned as socio technical infrastructures for collective problem solving. The rapid adoption of Generative AI (GenAI) introduces both complementarity and substitution. Large language models (LLMs) offer faster, more accessible drafts, yet divert traffic and contributions away from OKC that also provided their training data. To understand how communities adapt under this systemic shock, we report a mixed-methods study combining an online survey (N=217) and interviews with 11 current users. Findings show that while users increasingly rely on AI for convenience, they still turn to OKC for complex, ambiguous, or trust sensitive questions. Participants express polarized attitudes toward AI, reflecting divergent hopes and uncertainties about its role. Yet across perspectives, sustaining sociability,…
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