在线社交网络谣言传播的仿真研究——基于聚类系数可变的无标度网络环境

朱张祥; 刘咏梅; 朱张祥; 刘咏梅

doi:10.13306/j.1672-3813.2016.02.009

复杂系统与复杂性科学 >

2016 , Vol. 13 >Issue 2: 74 - 82

DOI: https://doi.org/10.13306/j.1672-3813.2016.02.009

在线社交网络谣言传播的仿真研究——基于聚类系数可变的无标度网络环境

朱张祥 ,
刘咏梅 ,
朱张祥 ,
刘咏梅

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中南大学商学院, 长沙 410083

朱张祥(1987-),男,安徽安庆人,博士研究生,主要研究方向为信息管理与网络舆情。

收稿日期: 2014-06-08

修回日期: 2014-10-24

网络出版日期: 2025-02-25

基金资助

国际(地区)合作与交流项目(71210003);2011年教育部“新世纪优秀人才支持计划”(NCET-11-0519);教育部博士点基金(20110162110065)

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Simulation Study of Propagation of Rumor in Online Social Network Based on Scale-Free Network with Tunable Clustering

ZHU Zhangxiang ,
LIU Yongmei ,
ZHU Zhangxiang ,
LIU Yongmei

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Business School, Central South University, Changsha 410083, China

Received date: 2014-06-08

Revised date: 2014-10-24

Online published: 2025-02-25

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摘要

在经典SIR传染病模型的基础上,根据在线社交网络中谣言传播的特点,将网络谣言的受众用户扩展为无知者、知晓者、信任者、传播者、暂时免疫者和永久免疫者6类。同时考虑到用户会因为不断接触某一相同的谣言而导致对该谣言的信任水平增加的现实情况,引入社会加强正向效应,提出了一个改进的在线社交网络谣言传播模型,并结合复杂网络的相关理论建立了一个考虑聚类系数可变的无标度网络环境进行仿真研究。仿真发现,谣言的传播能力与影响范围会随着社会加强正向效应、用户首次接触并相信谣言的概率、孤立节点密度以及初始传播节点的度的增大而增大,但会随着网络聚类系数的增加而得到抑制。本文提出的谣言传播模型比较符合真实在线社交网络的谣言传播特性,可以为实践中网络谣言的管控提供一定理论参考。

关键词： 网络谣言; 在线社交网络; 无标度网络; 聚类系数; 社会加强正向效应

本文引用格式

朱张祥 , 刘咏梅 , 朱张祥 , 刘咏梅 . 在线社交网络谣言传播的仿真研究——基于聚类系数可变的无标度网络环境[J]. 复杂系统与复杂性科学, 2016 , 13(2) : 74 -82 . DOI: 10.13306/j.1672-3813.2016.02.009

Abstract

Based on the rumor spreading characteristics of classic infection model (SIR) on real online social networks, this paper divides the OSN users into 6 different kinds of people, including the ignorants, the knowns, the believers, the spreaders, the temporary stiflers and the permanent stiflers. Taking into account the reality that people enhance their believing level when they contact with the same rumor constantly, this paper combines the positive effects of social reinforcement with the theory of complex networks to construct an improved rumor propagation model of online social network in the scale-free network environment considering tunable clustering. Numerical simulation results show that the rumor spreading range and ability will increase in the rumor first-believing probability, the degree of initial spreader nodes, the density of isolated node and the positive effects of social reinforcement; but on the contrary, it will be restrained by the increase of cluster coefficient. The improved rumor propagation model we proposed well fits the rumor spreading characteristics on real online social network and some theory references will be applied to manage and control Internet rumors.

Key words： Internet rumors; online social network; scale-free network; cluster coefficient; positive effects of social reinforcement

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