When AI summarizes the community: how generative AI summaries shape users’ intention to engage with original content

IF 7.2 3区管理学 Q1 BUSINESS

Internet Research Pub Date : 2026-09-21 DOI:10.1108/intr-10-2025-1763

Qian Liu,Shuang Wu,Lin Xu

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引用次数: 0

Abstract

Purpose The integration of Generative Artificial Intelligence (GenAI) into user-generated content (UGC) communities has fundamentally reshaped how users seek and consume information. Many UGC platforms, such as RedNote and Zhihu, now incorporate GenAI summaries that provide concise, AI-generated answers at the top of search results. While these summaries improve efficiency, they may also reduce user attention to original community posts, thereby threatening engagement and participation within UGC ecosystems. This study aims to examine how GenAI summary design influences users’ intention to engage with community content and the underlying psychological mechanisms. Design/methodology/approach Drawing on Socio-Technical Systems Theory (STS), this research develops a socio-cognitive model linking AI summary design (source localness and source transparency) to engagement intentions through collective psychological ownership and interest-type curiosity. Two online experiments were conducted: Experiment 1 tested the main and mediating effects, and Experiment 2 introduced query type (subjective-experiential vs objective-analytic) as a contextual moderator. Findings Results reveal two socio-cognitive pathways linking GenAI summary design to user engagement. Community-focused and aggregate-list summaries enhance engagement via collective ownership, whereas web-wide and item-level citation summaries foster curiosity-driven engagement. These effects are contingent on query type: subjective-experiential queries strengthen the ownership pathway, while objective-analytic queries amplify the curiosity pathway. Originality/value This study extends STS to AI-mediated content ecosystems by conceptualizing GenAI summaries as socio-technical interfaces. It advances our understanding of how interface-level design transforms technological affordances into social and cognitive motivations that sustain participation in digital communities.

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当AI总结社区：生成式AI总结如何塑造用户参与原创内容的意愿

将生成式人工智能（GenAI）集成到用户生成内容（UGC）社区中，从根本上重塑了用户寻找和消费信息的方式。许多UGC平台，如RedNote和知乎，现在都整合了GenAI摘要，在搜索结果的顶部提供简洁的人工智能生成的答案。虽然这些摘要提高了效率，但它们也可能减少用户对原始社区帖子的关注，从而威胁到UGC生态系统的参与度。本研究旨在探讨GenAI摘要设计如何影响用户参与社区内容的意愿及其潜在的心理机制。借鉴社会技术系统理论（STS），本研究开发了一种社会认知模型，通过集体心理所有权和兴趣型好奇心将人工智能概要设计（来源局域性和来源透明度）与参与意图联系起来。我们进行了两个在线实验：实验1测试了主效应和中介效应，实验2引入了查询类型（主观-经验vs客观-分析）作为语境调节因子。研究结果揭示了GenAI摘要设计与用户参与度之间的两种社会认知途径。以社区为中心和汇总列表摘要通过集体所有权增强参与度，而网络范围和项目级引文摘要则培养好奇心驱动的参与度。这些影响取决于查询类型：主观经验查询加强了所有权途径，而客观分析查询放大了好奇心途径。独创性/价值本研究通过将GenAI摘要概念化为社会技术接口，将STS扩展到人工智能介导的内容生态系统。它促进了我们对界面级设计如何将技术支持转化为维持数字社区参与的社会和认知动机的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Internet Research 工程技术-电信学

CiteScore

11.20

自引率

10.20%

发文量

审稿时长

>12 weeks

期刊介绍： This wide-ranging interdisciplinary journal looks at the social, ethical, economic and political implications of the internet. Recent issues have focused on online and mobile gaming, the sharing economy, and the dark side of social media.