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一种基于用户相对权重的在线社交网络信息传播模型

王金龙 刘方爱 朱振方

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一种基于用户相对权重的在线社交网络信息传播模型

王金龙, 刘方爱, 朱振方

An information spreading model based on relative weight in social network

Wang Jin-Long, Liu Fang-Ai, Zhu Zhen-Fang
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  • 根据在线社交网络信息传播特点和目前社交网络传播模型研究中存在的问题, 本文定义了网络用户之间的相互影响力函数, 在此基础上提出了一种基于用户相对权重的社交网络信息传播模型, 并对网络中的传播路径及传播过程进行了分析, 讨论了不同路径的信息传播影响力.为验证模型的有效性, 将传统的SIR模型和本文模型在六类不同网络拓扑下进行了仿真实验.仿真结果表明, 两类模型在均匀网络中没有明显差异, 但在非均匀网络中本文模型更能体现真实网络特点, 实验同时验证了节点的地位影响着信息的传播, 并且发现英文社交平台Twitter和中文社交平台新浪微博在拓扑结构上具备一定相似性.
    In this paper, we first introduce a mutual influence function among network nodes based on characteristics of information spreading in online social network. Then we put forward an information spreading model based on relative weight, analyze the propagation path and process of the network, and discuss the influence on different paths. Finally, the simulation experiments of the traditional SIR model and the model in this paper are conducted with six different network topologies. Results show that the two models have no significant difference in homogeneous networks, but there are significant differences in inhomogeneous networks. This result shows that the information spreading is influenced by the status of spreading nodes, and also shows that the real networks like Twitter and Sina Microblog have certain similarity in topological structure.
    • 基金项目: 山东省科技发展计划(批准号: 2013YD01045)、山东省优秀中青年科学家奖励基金(批准号: BS2013DX033)和教育部人文社科基金(批准号: 14YJC860042)资助的课题.
    • Funds: Project supported by the Shandong Province Foundation for Development of Science and Technology, China (Grant No. 2013YD01045), the Shandong Province Outstanding Young Scientist Award Fund, China (Grant No. BS2013DX033), and the Science Foundation of Ministry of Education of China (Grant No. 14YJC86004).
    [1]

    Newman M E J, Forest S, Balthrop J 2002 Phys. Rev. E 66 035101

    [2]

    Lloyd A L, May R M 2001 Science 292 1316

    [3]

    Yang L X, Yang X, Liu J, Zhu Q, Gan C 2013 Applied Mathematics and Computation 219 8705

    [4]

    Zhao L J, Cui H X, Qiu X Y, Wang X L, Wang J J 2013 Phys. A 392 995

    [5]

    Wang H, Han J H, Deng L, Cheng K Q 2013 Acta Phys. Sin. 62 110505 (in Chinese) [王辉, 韩江洪, 邓林, 程克勤 2013 物理学报 62 110505]

    [6]

    Gu Y R, Ge L L 2012 Acta Phys. Sin. 61 238701 (in Chinese) [顾亦然, 葛玲玲 2012 物理学报 61 238701]

    [7]

    Doerr B, Fouz M, Friedrich T 2012 Communications of the ACM 55 70

    [8]

    Chierichetti F, Lattanzi S, Panconesi A 2011 Theoretical Computer Science 412 2602

    [9]

    Doerr B, Fouz M, Friedrich T 2011 Proceedings of the 43rd annual ACM symposium on Theory of computing, San Jose, California, USA, June 6–8 2011 p21

    [10]

    Gong Y W, Song Y R, Jiang G P 2012 Chin. Phys. B 21 010205

    [11]

    Lu Y L, Jiang G P, Song Y R 2012 Chin. Phys. B 21 100207

    [12]

    Yuan X P, Xue Y K, Liu M X 2013 Chin. Phys. B 22 030207

    [13]

    Zhang Y C, Liu Y, Zhang H F, Cheng H, Xiong F 2011 Acta Phys. Sin. 60 050501 (in Chinese) [张彦超, 刘云, 张海峰, 程辉, 熊菲 2011 物理学报 60 050501]

    [14]

    Wang C, Liu C Y, Hu Y P, Liu Z H, Ma J F 2014 Acta Phys. Sin. 63 180501 (in Chinese) [王超, 刘骋远, 胡远萍, 刘志宏, 马建峰 2014 物理学报 63 180501]

    [15]

    Zheng M H, L L Y, Zhao M 2013 Physical Review E 88 012818

    [16]

    Lu L Y, Chen D B, Zhou T 2011 New Journal of Physics 13 123005

    [17]

    Liu C, Zhang Z K 2014 Communications in Nonlinear Science and Numerical Simulation 19 896

    [18]

    Ma Z E, Zhou Y C, Wang W D 2004 The mathematical theory of infectious diseases and its applications (Beijing: Science Press) pp4-5 (in Chinese) [马知恩, 周义仓, 王稳地 2004 传染病动力学的数学建模与研究(北京: 科学出版社)第4–5页 ]

    [19]

    Erdős P, Rényi A 1960 Publication of the Mathematical Institude of the Hungarian Academy of Sciences 5 17

    [20]

    Newman M E J, Watts D J 1999 Physics Letters A 263 341

    [21]

    Barrat A L, Albert R 1999 Science 286 509

  • [1]

    Newman M E J, Forest S, Balthrop J 2002 Phys. Rev. E 66 035101

    [2]

    Lloyd A L, May R M 2001 Science 292 1316

    [3]

    Yang L X, Yang X, Liu J, Zhu Q, Gan C 2013 Applied Mathematics and Computation 219 8705

    [4]

    Zhao L J, Cui H X, Qiu X Y, Wang X L, Wang J J 2013 Phys. A 392 995

    [5]

    Wang H, Han J H, Deng L, Cheng K Q 2013 Acta Phys. Sin. 62 110505 (in Chinese) [王辉, 韩江洪, 邓林, 程克勤 2013 物理学报 62 110505]

    [6]

    Gu Y R, Ge L L 2012 Acta Phys. Sin. 61 238701 (in Chinese) [顾亦然, 葛玲玲 2012 物理学报 61 238701]

    [7]

    Doerr B, Fouz M, Friedrich T 2012 Communications of the ACM 55 70

    [8]

    Chierichetti F, Lattanzi S, Panconesi A 2011 Theoretical Computer Science 412 2602

    [9]

    Doerr B, Fouz M, Friedrich T 2011 Proceedings of the 43rd annual ACM symposium on Theory of computing, San Jose, California, USA, June 6–8 2011 p21

    [10]

    Gong Y W, Song Y R, Jiang G P 2012 Chin. Phys. B 21 010205

    [11]

    Lu Y L, Jiang G P, Song Y R 2012 Chin. Phys. B 21 100207

    [12]

    Yuan X P, Xue Y K, Liu M X 2013 Chin. Phys. B 22 030207

    [13]

    Zhang Y C, Liu Y, Zhang H F, Cheng H, Xiong F 2011 Acta Phys. Sin. 60 050501 (in Chinese) [张彦超, 刘云, 张海峰, 程辉, 熊菲 2011 物理学报 60 050501]

    [14]

    Wang C, Liu C Y, Hu Y P, Liu Z H, Ma J F 2014 Acta Phys. Sin. 63 180501 (in Chinese) [王超, 刘骋远, 胡远萍, 刘志宏, 马建峰 2014 物理学报 63 180501]

    [15]

    Zheng M H, L L Y, Zhao M 2013 Physical Review E 88 012818

    [16]

    Lu L Y, Chen D B, Zhou T 2011 New Journal of Physics 13 123005

    [17]

    Liu C, Zhang Z K 2014 Communications in Nonlinear Science and Numerical Simulation 19 896

    [18]

    Ma Z E, Zhou Y C, Wang W D 2004 The mathematical theory of infectious diseases and its applications (Beijing: Science Press) pp4-5 (in Chinese) [马知恩, 周义仓, 王稳地 2004 传染病动力学的数学建模与研究(北京: 科学出版社)第4–5页 ]

    [19]

    Erdős P, Rényi A 1960 Publication of the Mathematical Institude of the Hungarian Academy of Sciences 5 17

    [20]

    Newman M E J, Watts D J 1999 Physics Letters A 263 341

    [21]

    Barrat A L, Albert R 1999 Science 286 509

计量
  • 文章访问数:  5509
  • PDF下载量:  1271
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-08-11
  • 修回日期:  2014-10-10
  • 刊出日期:  2015-03-05

一种基于用户相对权重的在线社交网络信息传播模型

  • 1. 山东师范大学信息科学与工程学院, 济南 250014;
  • 2. 山东省分布式计算机软件新技术重点实验室, 济南 250014;
  • 3. 山东交通学院信息科学与电气工程学院, 济南 250357
    基金项目: 山东省科技发展计划(批准号: 2013YD01045)、山东省优秀中青年科学家奖励基金(批准号: BS2013DX033)和教育部人文社科基金(批准号: 14YJC860042)资助的课题.

摘要: 根据在线社交网络信息传播特点和目前社交网络传播模型研究中存在的问题, 本文定义了网络用户之间的相互影响力函数, 在此基础上提出了一种基于用户相对权重的社交网络信息传播模型, 并对网络中的传播路径及传播过程进行了分析, 讨论了不同路径的信息传播影响力.为验证模型的有效性, 将传统的SIR模型和本文模型在六类不同网络拓扑下进行了仿真实验.仿真结果表明, 两类模型在均匀网络中没有明显差异, 但在非均匀网络中本文模型更能体现真实网络特点, 实验同时验证了节点的地位影响着信息的传播, 并且发现英文社交平台Twitter和中文社交平台新浪微博在拓扑结构上具备一定相似性.

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