计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 230-235.doi: 10.11896/jsjkx.190400164

• 人工智能 • 上一篇    下一篇

结合非完全信息博弈的SIR传播模型

包峻波, 闫光辉, 李俊成   

  1. 兰州交通大学电子与信息工程学院 兰州730070
  • 收稿日期:2019-04-29 出版日期:2020-06-15 发布日期:2020-06-10
  • 通讯作者: 闫光辉(yanghacademic@163.com)
  • 作者简介:543010129@qq.com
  • 基金资助:
    国家自然科学基金(61662066,61163010);甘肃省青年基金(1606RJYA222)

SIR Propagation Model Combing Incomplete Information Game

BAO Jun-bo, YAN Guang-hui, LI Jun-cheng   

  1. School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
  • Received:2019-04-29 Online:2020-06-15 Published:2020-06-10
  • About author:BAO Jun-bo,born in 1994,postgradua-te.His main research interests include propagation dynamics of complex networks.
    YANG Guang-hui,born in 1970,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include database theory and system,Internet of things engineering and application,data mi-ning,complex network analysis,etc.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61662066,61163010) and Foundation for Young Scholars of GansuProvince, China (1606RJYA222)

摘要: 社交网络已成为现代社会人们交往的重要形式,社交网络中的信息传播调控机制已成为当前研究领域的热点。考虑到社会中信息真伪的不确定性,文中引入博弈论(game theory)和社会加强效应(social strengthening effect)精确刻画信息在传播过程中的扩散概率,突出节点在信息传播中的个体差异,从博弈的角度考虑在不同的真假消息背景下,不同传播概率对节点传播情况的影响,结合非完全信息博弈刻画基础传播概率,根据社会加强效应对基础传播概率进行调整,设计并研究了基于非完全信息博弈的SIR传播模型,并基于小世界模型、无标度模型与实际网络数据集进行仿真,从网络模型类型、网络大小、传播概率等方面进行仿真实验。实验结果表明,提出的传播模型丰富了社交网络消息传播控制与免疫的研究技术,社会加强效应有较好的促进传播效果。

关键词: SIR, 博弈论, 纳什均衡, 社会加强效应, 信息传播

Abstract: Social networks have become an important form of people’s communication in modern society.The information transmission and control mechanism in social networks has become a hot topic in the current research field.Taking into account the uncertainty of information authenticity in society,this paper introduces game theory and social reinforcement effect to accurately describe the diffusion probability of information in the process of communication,highlights the individual differences of nodes in the process of information propagation, and considers the impact of different propagation probabilities on the propagation of nodes in the context of different true and false messages from a game perspective,combines with incomplete information game to describe the basic propagation probability,and then adjusts the basic propagation probability according to social reinforcement effect,designs and studies the SIR propagation model based on incomplete information game.And based on the small world mo-del,the scale-free model and the actual network data set to simulate,from the network model type,network size,propagation probability and other aspects of experiments.The results show that the proposed propagation model enriches the research techniques of message communication control and immunity in social networks,and the social reinforcement effect has a good effect on communication.

Key words: Game theory, Information dissemination, Nash equilibrium, SIR, Social strengthening effect

中图分类号: 

  • TP393.01
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