RESEARCH PAPERS

Social Bots in Human-AI Interaction: A Study of the Manipulation Mechanisms of User Engagement Behaviors by Sentiment Polarity

  • Cheng Qingxuan ,
  • Xu Hao ,
  • Dong Jing ,
  • Liang Shaobo
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  • 1 School of New Media, Peking University, Beijing 100871;
    2 School of Information Management, Central China Normal University, Wuhan 430079;
    3 School of Information Management, Wuhan University, Wuhan 430072

Received date: 2024-12-10

  Revised date: 2025-05-07

  Online published: 2026-01-16

Supported by

This work is supported by the National Natural Science Foundation of China project titled “Research on Interpretable Intelligent Decision Making Methods Driven by both Data and Knowledge from the Perspective of Human-Computer Interaction”(Grant No. 92370112).

Abstract

[Purpose/Significance] As agents in HAII, social bots influence user behaviors through sentimental manipulation. Clarifying the impact of social bots’ comments sentiment polarity on user engagement helps to understand the manipulation mechanism and provides theoretical support for the development of effective social bots regulatory strategies. [Method/Process] Based on Weibo, this study designed an online experimental scenario using comments with different sentimental polarities(positive, neutral, and negative) posted by “Comment Robert” as the experimental materials. A total of 305 participants were recruited through a questionnaire survey. It systematically examined the differences in user engagement behaviors under different sentimental polarities, the direct impact of sentiment polarity on user engagement, and the moderating effect of perceived anthropomorphism. [Result/Conclusion] Positive sentiment polarity significantly promotes “like/share”, while users prefer “reply” under negative and neutral sentiment polarity. Perceived anthropomorphism has a significant impact on overall user engagement behaviors, but fails to moderate the relationship between sentiment polarity and user behavior. In addition, the sentiment polarity of users’ replies tends to be more positive in the presence of negative sentiment polarity. These findings reveal the mechanism by which social bots influence user behavior through sentimental manipulation, enrich the understanding of HAII, and provide important theoretical support for social bots’ design and regulation.

Cite this article

Cheng Qingxuan , Xu Hao , Dong Jing , Liang Shaobo . Social Bots in Human-AI Interaction: A Study of the Manipulation Mechanisms of User Engagement Behaviors by Sentiment Polarity[J]. Library and Information Service, 2026 , 70(1) : 56 -68 . DOI: 10.13266/j.issn.0252-3116.2026.01.005

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