计算机应用 ›› 2017, Vol. 37 ›› Issue (4): 1083-1087.DOI: 10.11772/j.issn.1001-9081.2017.04.1083

• 人工智能 • 上一篇    下一篇

基于节点亲密度和影响力的社交网络舆论形成模型

张亚楠, 孙士保, 张京山, 尹立航, 闫晓龙   

  1. 河南科技大学 信息工程学院, 河南 洛阳 471023
  • 收稿日期:2016-09-14 修回日期:2016-12-25 出版日期:2017-04-10 发布日期:2017-04-19
  • 通讯作者: 孙士保
  • 作者简介:张亚楠(1991-),男,河南西平人,硕士研究生,主要研究方向:网络舆情、数字图像处理;孙士保(1970-),男,河南信阳人,教授,博士,主要研究方向:计算机网络、数字图像处理;张京山(1992-),男,河南洛阳人,硕士研究生,主要研究方向:计算机网络、网络舆情;尹立航(1991-),男,河南新乡人,硕士研究生,主要研究方向:网络舆情;闫晓龙(1990-),男,河南洛阳人,硕士研究生,主要研究方向:网络舆情。
  • 基金资助:
    河南省重点攻关项目(152102210277);河南省产学研合作计划项目(152107000027);河南省高校科技创新团队支持计划项目(17IRTSTHN010);河南科技大学科技创新团队项目(2015XTD011);河南科技大学重大产学研合作培育基金资助项目(2015ZDCXY03)。

Opinion formation model of social network based on node intimacy and influence

ZHANG Yanan, SUN Shibao, ZHANG Jingshan, YIN Lihang, YAN Xiaolong   

  1. College of Information Engineering, Henan University of Science & Technology, Luoyang Henan 471023, China
  • Received:2016-09-14 Revised:2016-12-25 Online:2017-04-10 Published:2017-04-19
  • Supported by:
    This work is partially supported by Key Projects of Henan Province (152102210277), the Industry-Academia-Research Cooperation Projects of Henan Province (152107000027), the Program for Innovative Research Team (in Science and Technology) in University of Henan Province(17IRTSTHN010), the Technological Innovation Team of Henan University of Science and Technology (2015XTD011), the Major Cooperative Engagement Fund of Henan University of Science and Technology (2015ZDCXY03).

摘要: 针对舆论传播过程中个体交互的广泛性和个体社会影响力的差异性,在Hegselmann-Krause模型的基础上建立了社交网络舆论形成模型。新模型通过引入个体间亲密度、人际相似性和交互强度等概念,对个体交互集合进行了扩展,并对影响力权重进行了合理量化,进而构建更切合实际的观点交互规则。通过一系列仿真实验,分析了模型主要参数在舆论演化中的作用。结果表明:在不同信任阈值下,群体观点均能收敛到一致,形成舆论共识;且信任阈值越大,收敛时间越短;当信任阈值为0.2时,收敛时间仅为10。同时,扩大交互集合、提高人际相似性的作用强度会促进舆论共识的形成。此外,当无标度网络的聚类系数和平均度较高时,群体观点更容易产生趋同效应。研究结果有助于理解舆论形成的动力学过程,对社会管理者进行决策分析具有指导作用。

关键词: 社交网络, 舆论形成, 共识, 亲密度, 人际相似性, 交互强度

Abstract: Aiming at the universality of individual interaction and the heterogeneity of individual social influence in opinion spreading, an opinion formation model of social network was proposed on the basis of Hegselmann-Krause model. By introducing the concepts of intimacy between individuals, interpersonal similarity and interaction strength, the individual interactive set was extended, the influence weight was reasonably quantified, and more realistic view of interaction rule was built. Through a series of simulation experiments, the effects of main parameters in the model on opinion evolution were analyzed. The simulation results indicate that group views can converge to the same and form consensus under different confidence thresholds. And the larger the confidence threshold is, the shorter the convergence time is. When confidence threshold is 0.2, convergence time is only 10. Meanwhile, extending the interactive set and increasing the strength of interpersonal similarity will promote consensus formation. Besides, when the clustering coefficient and the average degree of scale-free network are higher, the group views are more likely to produce convergence effect. The results are helpful to understand the dynamic process of opinion formation, and can guide social managers to make decisions and analysis.

Key words: social network, opinion formation, consensus, intimacy, interpersonal similarity, interaction strength

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