基于社团结构的多层复杂网络中信息传播机制研究
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摘要
[目的/意义]信息传播渠道的增加使得单层模式的复杂网络不再适用,多层复杂网络逐渐得到重视。[方法/过程]文章基于系统动力学中的信息包传输,引入社团结构概念,设定基于社团结构的多层复杂网络。通过对层间社团结构的相似度、初始节点的数量、社团中位置以及所处网络等参数进行调节,对多层复杂网络的信息传播机制进行研究。[结果/结论]研究发现,信息的传播规模与初始节点数量成正比;初始节点处于线上网络的传播速度快于线下网络,但对最终传播规模影响不大;连接两个社团的"信息交换者"作为初始节点,最终信息的爆发规模扩大显著;调节多层网络中的社团结构稀疏程度会影响信息的传播范围,社团结构越稀疏,传播规模反而越大。[局限]信息的传播对多层网络的结构也会形成影响,但模型未考虑其相互作用。
[Purpose/significance] The increase of information dissemination channels has made the complex network of single layer model no longer applicable,and the multi-layer complex network has been gradually taken seriously.[Method/process] Based on the information packet transmission in system dynamics,this paper introduces the concept of community structure and sets up a multi-layer complex network based on community structure.The information dissemination mechanism of the multi-layer complex network is studied by adjusting the similarity of the inter layer community structures,the number of initial burst nodes,the position of the community and the network.[Result/conclusion] Results show that the size of the information dissemination is proportional to the number of nodes in the initial propagation,the initial nodes of the online network spread faster than the offline network,but this has little effect on the final transmission scale,When the "information exchanger" of two communities functions as the initial node,the size of the final information burst expands greatly,and the sparsity degree of community structure which regulates multi-layer network has an influence on the spread scope of information,the more sparse the community structure is,the larger the diffusion scale is.[Limitations] The propagation of information also affects the structure of the multi-layer network,but the model does not consider its interaction.
[Purpose/significance] The increase of information dissemination channels has made the complex network of single layer model no longer applicable,and the multi-layer complex network has been gradually taken seriously.[Method/process] Based on the information packet transmission in system dynamics,this paper introduces the concept of community structure and sets up a multi-layer complex network based on community structure.The information dissemination mechanism of the multi-layer complex network is studied by adjusting the similarity of the inter layer community structures,the number of initial burst nodes,the position of the community and the network.[Result/conclusion] Results show that the size of the information dissemination is proportional to the number of nodes in the initial propagation,the initial nodes of the online network spread faster than the offline network,but this has little effect on the final transmission scale,When the "information exchanger" of two communities functions as the initial node,the size of the final information burst expands greatly,and the sparsity degree of community structure which regulates multi-layer network has an influence on the spread scope of information,the more sparse the community structure is,the larger the diffusion scale is.[Limitations] The propagation of information also affects the structure of the multi-layer network,but the model does not consider its interaction.
引文
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[3] 周奇,陆敬筠,朱晓峰.基于社交团体和用户相似度的信息推荐方法[J].情报理论与实践,2016,39(1):123-127.
[4] 肖雪,陈云伟,邓勇.基于节点内容及拓扑结构的引文网络社团划分[J].图书情报知识,2017(1):89-97.
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[10] TIAN R Y,ZHANG X F,LIU Y J.SSIC model:a multi-layer model for intervention of online rumors spreading[J].Physica A Statistical Mechanics & Its Applications,2015,427:181.
[11] SHANG J,LIU L,LI X,et al.Epidemic spreading on complex networks with overlapping and non-overlapping community structure[J].Physica A Statistical Mechanics & Its Applications,2015,419(419):171-182.
[12] WANG Y,XIAO G.Epidemics spreading in interconnected complex networks[J].Physics Letters A,2012,376:2689-2696.
[13] 于凯.双层耦合网络上的信息传播模型研究[D].大连:大连理工大学,2015.
[14] DE D M,SOLéRIBALTA A,GóMEZ S,et al.Navigability of interconnected networks under random failures[J].Proceedings of the National Academy of Sciences of the United States of America,2014,111(23):8351.
[15] FORTUNATO S.Community detection in graphs[J].Physics Reports,2010,486:75-174.
[16] ARENAS A,DíAZ-GUILERA A,PéREZ-VICENTE C J.Synchronization reveals topological scales in complex networks[J].Physical Review Letters,2006,96(11):114102.
[17] 孙海生.连边社团检测算法对共词分析聚类结果的改进研究[J].图书情报工作,2016(10):123-129.
[18] NEWMAN M E J,GIRVAN M.Finding and evaluating community structure in networks[J].Physical Review E Statistical Nonlinear & Soft Matter Physics,2010,69(2):026113-026113.
(12):7821-7826.
[2] 汪小帆,李翔,陈关荣.复杂网络理论及其应用[M].北京:清华大学出版社,2006:162-191.
[3] 周奇,陆敬筠,朱晓峰.基于社交团体和用户相似度的信息推荐方法[J].情报理论与实践,2016,39(1):123-127.
[4] 肖雪,陈云伟,邓勇.基于节点内容及拓扑结构的引文网络社团划分[J].图书情报知识,2017(1):89-97.
[5] 赵之滢,于海,朱志良,等.基于网络社团结构的节点传播影响力分析[J].计算机学报,2014(4):753-766.
[6] 朱晓霞,赵雪,刘萌萌.基于社团结构的节点的影响力分析[J].计算机应用研究,2017,34(9):2582-2585.
[7] RAPOPORT A,REBHUN L.0n the mathematical theory of rumor spread[J].Bulletin of Mathematical Biology,1952,14(4):375-383.
[8] ZHAO L,WANG X,WANG J,et al.Rumor-propagation model with consideration of refutation mechanism in homogeneous social networks[J].Discrete Dynamics in Nature & Society,2014:1-11.
[9] 钟琪,戚巍,张乐.Lotka-Volterra系统下的社会型危机信息扩散模型[J].系统工程理论与实践,2012,32(1):104-110.
[10] TIAN R Y,ZHANG X F,LIU Y J.SSIC model:a multi-layer model for intervention of online rumors spreading[J].Physica A Statistical Mechanics & Its Applications,2015,427:181.
[11] SHANG J,LIU L,LI X,et al.Epidemic spreading on complex networks with overlapping and non-overlapping community structure[J].Physica A Statistical Mechanics & Its Applications,2015,419(419):171-182.
[12] WANG Y,XIAO G.Epidemics spreading in interconnected complex networks[J].Physics Letters A,2012,376:2689-2696.
[13] 于凯.双层耦合网络上的信息传播模型研究[D].大连:大连理工大学,2015.
[14] DE D M,SOLéRIBALTA A,GóMEZ S,et al.Navigability of interconnected networks under random failures[J].Proceedings of the National Academy of Sciences of the United States of America,2014,111(23):8351.
[15] FORTUNATO S.Community detection in graphs[J].Physics Reports,2010,486:75-174.
[16] ARENAS A,DíAZ-GUILERA A,PéREZ-VICENTE C J.Synchronization reveals topological scales in complex networks[J].Physical Review Letters,2006,96(11):114102.
[17] 孙海生.连边社团检测算法对共词分析聚类结果的改进研究[J].图书情报工作,2016(10):123-129.
[18] NEWMAN M E J,GIRVAN M.Finding and evaluating community structure in networks[J].Physical Review E Statistical Nonlinear & Soft Matter Physics,2010,69(2):026113-026113.