网络结构影响传播效果的解耦分析

doi:10.11896/jsjkx.220900113

计算机科学 ›› 2023, Vol. 50 ›› Issue (7): 368-375.doi: 10.11896/jsjkx.220900113

网络结构影响传播效果的解耦分析

崔允松¹, 吴晔^2,3, 许小可¹

1 大连民族大学信息与通信工程学院辽宁大连 116000
2 北京师范大学计算传播学研究中心广东珠海 519085
3 北京师范大学新闻传播学院北京 100875

收稿日期:2022-09-13 修回日期:2022-11-22 出版日期:2023-07-15 发布日期:2023-07-05
通讯作者: 许小可(xuxiaoke@foxmail.com)
作者简介:(337579873@qq.com)
基金资助:
国家自然科学基金(62173065);辽宁省自然科学基金(2020-MZLH-22)

Decoupling Analysis of Network Structure Affecting Propagation Effect

CUI Yunsong¹, WU Ye^2,3, XU Xiaoke¹

1 School of Information and Communication Engineering,Dalian Minzu University,Dalian,Liaoning 116000,China
2 Research Center of Computational Communication,Beijing Normal University,Zhuhai,Guangdong 519085,China
3 School of Journalism and Communication,Beijing Normal University,Beijing 100875,China

Received:2022-09-13 Revised:2022-11-22 Online:2023-07-15 Published:2023-07-05
About author:CUI Yunsong,born in 1997,postgra-duate.His main research interests include null model of complex social network.XU Xiaoke,born in 1979,Ph.D,professor.His main research interests include network science and social network analysis.
Supported by:
National Natural Science Foundation of China(62173065) and Natural Science Foundation of Liaoning Province,China(2020-MZLH-22).

摘要/Abstract

摘要： 如今越来越多的人通过社交网络传播信息,在线社交网络逐渐改变了人们交换信息的方式,因此基于在线社交网络研究信息传播效果的影响因素受到众多研究人员的关注,尤其是网络结构对信息传播效果的影响。以往研究大都强调某种网络统计量对信息传播效果的影响,但各个网络统计量之间相互耦合的现象是客观存在的,某种网络统计量的改变可能导致其他网络统计量同步改变,从而可能影响最终的传播效果。提出一个解耦的零模型框架,通过零模型解耦不同网络统计量间的耦合作用,然后使用SIR传播模型仿真实验来分析网络统计量在没有耦合作用下对信息传播效果的影响,最后使用线性阈值模型仿真实验验证SIR模型的实验结论在社会强化中的适用性。通过Facebook和Twitter实证网络的传播模型仿真实验表明:网络的平均最短路径是影响信息传播速度和信息传播范围的主要因素,聚类系数是影响信息传播范围的次要因素。

关键词: 传播效果, 零模型, 平均最短路径, 聚类系数

Abstract: As more and more people spread information through social networks,online social networks have gradually changed the way people exchange information,so the influencing factors of information dissemination effect based on online social networks have attracted the attention of many researchers,especially the influence of network structure on the effect of information dissemination.In previous studies,most of the research has emphasized the influence of a certain network statistic on the effect of information dissemination,but the phenomenon of coupling between various network statistics is objective,and the change of a certain network statistic may lead to synchronous changes of other network statistics,which may affect the final propagation effect.In this study,a decoupled zero model framework is proposed,which decouples the coupling between different network statistics through the zero model,and then uses the SIR propagation model simulation experiment to analyze the influence of network statistics on information propagation effect without coupling,and finally uses linear threshold model simulation experiments to verify the applicability of the experimental conclusions of the SIR model in social reinforcement.Simulation experiments of the propagation model of Facebook and Twitter empirical networks show that the average shortest path of the network is the main factor affecting the speed and scope of information dissemination,and the clustering coefficient is the secondary factor affecting the scope of information dissemination.

Key words: Propagation effect, Null model, Average shortest path length, Clustering coefficient

中图分类号:

TP301

崔允松, 吴晔, 许小可. 网络结构影响传播效果的解耦分析[J]. 计算机科学, 2023, 50(7): 368-375. https://doi.org/10.11896/jsjkx.220900113

CUI Yunsong, WU Ye, XU Xiaoke. Decoupling Analysis of Network Structure Affecting Propagation Effect[J]. Computer Science, 2023, 50(7): 368-375. https://doi.org/10.11896/jsjkx.220900113

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网络结构影响传播效果的解耦分析

Decoupling Analysis of Network Structure Affecting Propagation Effect

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