图书情报知识 ›› 2026, Vol. 43 ›› Issue (4): 68-79, 92.doi: 10.13366/j.dik.2026.04.068

• 学术聚焦(2)·AI幻觉 • 上一篇    下一篇

对抗AI幻觉:用户对GAI冲突性虚假信息的验证行为研究

常琳1, 柯青1, 叶凤云2   

  1. 1. 南京大学信息管理学院,南京,210023;
    2. 安徽大学管理学院,合肥,230601
  • 出版日期:2026-07-10 发布日期:2026-10-06
  • 通讯作者: 柯青(ORCID:0000-0002-6300-2682),博士,教授,研究方向:人机交互与用户行为,Email: keqing@nju.edu.cn。
  • 作者简介:常琳(ORCID: 0009-0000-9102-0039),博士研究生,研究方向:人机交互与用户行为,Email: 3271037630@qq.com;叶凤云(ORCID: 0000-0003-4466-109X),博士,教授,研究方向:网络信息行为,Email: 344707062@qq.com。
  • 基金资助:
    本文系国家自然科学基金面上项目“心理免疫视角下社交媒体虚假信息干预治理路径研究”(72474099)的研究成果之一。

Countering AI Hallucinations: A Research on Users' Verification Behavior Toward GAI Conflicting Misinformation

CHANG Lin1, KE Qing1, YE Fengyun2   

  1. 1. School of Information Management, Nanjing University, Nanjing, 210023;
    2. School of Management, Anhui University, Hefei, 230601
  • Online:2026-07-10 Published:2026-10-06
  • Contact: Correspondence should be addressed to KE Qing,Email: keqing@nju.edu.cn, ORCID: 0000-0002-6300-2682
  • Supported by:
    This is an outcome of the project "Research on the Intervention and Governance Path of Misinformation on Social Media from the Perspective of Psychological Immunity"(72474099)supported by National Natural Science Foundation of China.

摘要: [目的/意义] 探究GAI冲突性虚假信息情境下用户验证行为的动态演化机制,揭示其认知、情绪、行为变化过程,为AI幻觉治理提供人本视角的解决方案。[研究设计/方法]对34名GAI用户进行半结构化访谈,采用关键事件技术和深度访谈方法获取数据,利用扎根理论的程序化编码方式对质性材料进行编码分析,提炼出4个核心范畴和15个主范畴,构建用户验证行为动态演化模型。[结论/发现] 在GAI冲突性虚假信息情境中,用户验证行为主要沿三条路径演化:认知路径(情境触发—认知评价—验证行为)、情绪路径(情境触发—情绪反应—验证行为)和认知—情绪路径(情境触发—认知评价—情绪反应—验证行为)。在认知与情绪的共同作用下,用户会选择启发式验证或系统式验证,并且两种验证行为模式之间存在动态转化关系。同时,验证结果作为反馈会重塑初始情境,进而形成动态循环。[创新/价值]突破已有信息验证研究的静态视角,构建融合认知、情绪与行为的动态演化模型,明确了GAI情境下用户验证行为的多路径驱动机制与反馈重塑过程,拓展了HSM理论在人机交互场景下的适用边界。

关键词: 冲突性虚假信息, AI幻觉, 验证行为, 生成式人工智能, 启发式—系统式模型

Abstract: [Purpose/Significance] This study aims to explore the dynamic evolutionary mechanisms of users' verification behavior in the context of GAI-generated conflicting misinformation. By revealing the evolving processes across cognitive, emotional, and behavioral dimensions, it seeks to provide a human-centered solution for the governance of AI hallucinations. [Design/Methodology] Qualitative data were collected from 34 GAI users through semi-structured in-depth interviews combined with the Critical Incident Technique. Utilizing the systematic coding procedures of Grounded Theory, the qualitative materials were analyzed and coded, extracting 4 core categories and 15 main categories to construct a user-validated dynamic behavior evolutionary model. [Findings/Conclusion] In the context involving GAI-generated conflicting misinformation, user verification behavior primarily evolves along three distinct pathways: the cognitive path (contextual trigger–cognitive appraisal–verification behavior), the emotional path(contextual trigger–emotional response–verification behavior), and the cognitive–emotional path(contextual trigger–cognitive appraisal–emotional response–verification behavior). Driven jointly by cognition and emotion, users opt for either heuristic or systematic verification, with a dynamic transformation relationship existing between these two verification behavioral modes. Furthermore, the verification outcome serves as feedback that reshapes the initial context, thereby giving rise to a dynamic cycle. [Originality/Value] Moving beyond the static perspective inherent in existing information verification studies, this research constructs a dynamic evolutionary model that integrates cognition, emotion, and behavior. It elucidates the multi-pathway driving mechanisms and the feedback reshaping process underlying user verification behavior in GAI context, and extends the applicability boundaries of HSM theory in human–computer interaction scenarios.

Keywords: Conflicting misinformation, AI hallucinations, Verification behavior, Generated AI(GAI), Heuristic-Systematic Model