计算机与现代化 ›› 2024, Vol. 0 ›› Issue (09): 82-90.doi: 10.3969/j.issn.1006-2475.2024.09.014

• 数据库与数据挖掘 • 上一篇    下一篇

考虑时序特征的耦合网络环境下社交机器人的舆情引导


  


  1. (南京航空航天大学经济与管理学院,江苏 南京 211106)
  • 出版日期:2024-09-27 发布日期:2024-09-29
  • 基金资助:
    国家自然科学基金面上项目(72174086)

Public Opinion Guidance of Social Bots in Coupling Network Environment Considering Temporal Characteristics

  1. (School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)
  • Online:2024-09-27 Published:2024-09-29

摘要: 近年来,社交机器人作为社交网络生态中新的舆情参与主体备受关注。然而,国内对其研究相对不足。为深入了解社交机器人在舆情演化中发挥的作用和对应规律,有必要研究其对群体观点演化的影响。本文通过考虑个体活跃度变化表现出的霍克斯过程,构建社交网络连边时变的驱动机制。同时,搭建不对称双层耦合社交网络和对应的连续观点演化模型,并引入社交机器人研究其对群体观点的引导效果。实验分析发现,舆情事件在线上社交网络中的讨论升温后,引发了线下社交网络中群体活跃度的进一步增加,与实际情况相符。此外,极少数社交机器人也能有效引导群体观点,因此,设定一定数量的社交机器人并及早投入是有效引导舆论的策略之一。

关键词: 观点演化, 耦合网络, 时序网络, 舆情引导, 社交机器人

Abstract:  In recent years, social bots have garnered significant attention as new participants in the ecosystem of social networks. However, research on them within the country is relatively scarce. To gain in-depth insights into the role and corresponding patterns of social bots in the evolution of public opinion, it is necessary to investigate their impact on the evolution of group opinions. This study, by considering the Hawkes process manifested in individual activity changes, constructs a time-varying driving mechanism for the formation of social network connections. Simultaneously, it establishes an asymmetric two-layer coupled social network and the corresponding continuous opinion evolution model. The study introduces social bots and explores their guiding effects on group opinions. The experimental analysis reveals that the discussion in online social networks about public events heats up and triggers a further increase in the group activity level in offline social networks, aligning with real-world scenarios. Additionally, a very small number of social bots can effectively guide group opinions, demonstrating their practical value. Therefore, setting a certain number of social bots and deploying them early on is an effective strategy for guiding public opinion.

Key words:  , opinion evolution; coupled networks; temporal networks; opinion guidance; social bots

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