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基于在线社交网络的信息传播模型

张彦超 刘云 张海峰 程辉 熊菲

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基于在线社交网络的信息传播模型

张彦超, 刘云, 张海峰, 程辉, 熊菲

The research of information dissemination model on online social network

Zhang Yan-Chao, Liu Yun, Zhang Hai-Feng, Cheng Hui, Xiong Fei
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  • 本文构造了一个基于在线社交网络的信息传播模型.该模型考虑了节点度和传播机理的影响,结合复杂网络和传染病动力学理论,进一步建立了动力学演化方程组.该方程组刻画了不同类型节点随着时间的演化关系,反映了传播动力学过程受到网络拓扑结构和传播机理的影响.本文模拟了在线社交网络中的信息传播过程,并分析了不同类型节点在网络中的行为规律.仿真结果表明:由于在线社交网络的高度连通性,信息在网络中传播的门槛几乎为零;初始传播节点的度越大,信息越容易在网络中迅速传播;中心节点具有较大的社会影响力;具有不同度数的节点在网络中的变
    In this paper, we propose a general stochastic model for the information dissemination on the online social network. The model considers the node of degree and propagation mechanism, utilizes complex network theory and dynamics of infectious diseases, and finally establishes the dynamic evolution equations. The dynamic evolution equations describe the evolution process of different types of nodes, and show that the propagation process is influenced by network topology and propagation mechanism. We simulate the information spreading process, and analyze the behavior of different types of nodes on online social network. Simulation results show that information can spread easily on the online social network because of the good connectivity. The greater the degree of the initial spread node, the faster the information spreads on online social network. Center nodes have great social influence, and the nodes with different degrees have the similar trend on online social network. Research shows that the model, having the same characteristics with online social network, contributes to a more profound understanding of information dissemination behavior on online social network.
    • 基金项目: 国家自然科学基金(批准号:60972012),北京市自然科学基金(批准号:4102047),科技人员服务企业项目(批准号:2009GJA00048),教育部哲学人文社会科学研究重大课题(批准号:08WL1101)和北京市教育委员会学科建设与研究生建设项目资助的课题.
    [1]

    Hu H B, Wang X F 2009 Phys. Lett. A 37 1105

    [2]

    Song X D, Lin C Y, Tseng B L, Sun M T 2005 International Conference on Knowledge Discovery and Data Mining, Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, Chicago, Illinois, USA, August 21—24, 2005, 2005 p479

    [3]

    Hu H B, Han D Y, Wang X F 2010 Physica A 389 1065

    [4]

    Kumar R, Novak J, Tomkins A 2006 International Conference on Knowledge Discovery and Data Mining, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, Philadelphia, PA, USA, August 20—23, 2006 p611

    [5]

    Mislove A, Marcon M, Gummad K P 2007 Internet Measurement Conference, Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, San Diego, California, USA, October 24—26, 2007 p29

    [6]

    Chun H, Kwak H, Eom Y H, Ahn Y Y, Moon S, Jeong H 2008 Internet Measurement Conference, Proceedings of the 8th ACM SIGCOMM conference on Internet measurement, Vouliagmeni, Greece, October 20—22, 2008 p57

    [7]

    Ahn Y Y, Han S, Kwak H, Moon S, Jeong H 2007 International World Wide Web Conference, Proceedings of the 16th international conference on World Wide Web, Banff, Alberta, Canada, May 8—12, 2007 p835

    [8]

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

    [9]

    Ni S J, Weng W G, Fan W C 2009 Acta Phys. Sin. 58 3707 (in Chinese) [倪顺江、 翁文国、 范维澄 2009 58 3707]

    [10]

    Moreno Y, Nekovee M, Pacheco A F 2004 Phys. Rev. E 69 066130

    [11]

    Zanette D H 2002 Phys. Rev. E 65 041908

    [12]

    Zhang L, Liu Y 2008 Acta Phys. Sin. 57 5419 (in Chinese) [张 立、 刘 云 2008 57 5419]

    [13]

    Java A, Kolari P, Finin T, Oates T 2006 The 15th International World Wide Web Conference, Edinburgh, UK, May 22—26, 2006

    [14]

    Newman M E J 2002 Phys. Rev. Lett. 89 208701

    [15]

    Albert R, Barabási A L 2000 Phys. Rev. Lett. 85 5234

    [16]

    Newman M E J 2001 Phys. Rev. E 64 016132

    [17]

    Jeong H, Mason S P, Barabási A L, Oltvai Z N 2001 Nature 411 41

    [18]

    Fu F, Chen X J, Liu L H, Wang L 2007 arXiv: 0701323

    [19]

    Vázquez A, Weigt M 2003 Phys. Rev. E 67 027101

  • [1]

    Hu H B, Wang X F 2009 Phys. Lett. A 37 1105

    [2]

    Song X D, Lin C Y, Tseng B L, Sun M T 2005 International Conference on Knowledge Discovery and Data Mining, Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, Chicago, Illinois, USA, August 21—24, 2005, 2005 p479

    [3]

    Hu H B, Han D Y, Wang X F 2010 Physica A 389 1065

    [4]

    Kumar R, Novak J, Tomkins A 2006 International Conference on Knowledge Discovery and Data Mining, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, Philadelphia, PA, USA, August 20—23, 2006 p611

    [5]

    Mislove A, Marcon M, Gummad K P 2007 Internet Measurement Conference, Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, San Diego, California, USA, October 24—26, 2007 p29

    [6]

    Chun H, Kwak H, Eom Y H, Ahn Y Y, Moon S, Jeong H 2008 Internet Measurement Conference, Proceedings of the 8th ACM SIGCOMM conference on Internet measurement, Vouliagmeni, Greece, October 20—22, 2008 p57

    [7]

    Ahn Y Y, Han S, Kwak H, Moon S, Jeong H 2007 International World Wide Web Conference, Proceedings of the 16th international conference on World Wide Web, Banff, Alberta, Canada, May 8—12, 2007 p835

    [8]

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

    [9]

    Ni S J, Weng W G, Fan W C 2009 Acta Phys. Sin. 58 3707 (in Chinese) [倪顺江、 翁文国、 范维澄 2009 58 3707]

    [10]

    Moreno Y, Nekovee M, Pacheco A F 2004 Phys. Rev. E 69 066130

    [11]

    Zanette D H 2002 Phys. Rev. E 65 041908

    [12]

    Zhang L, Liu Y 2008 Acta Phys. Sin. 57 5419 (in Chinese) [张 立、 刘 云 2008 57 5419]

    [13]

    Java A, Kolari P, Finin T, Oates T 2006 The 15th International World Wide Web Conference, Edinburgh, UK, May 22—26, 2006

    [14]

    Newman M E J 2002 Phys. Rev. Lett. 89 208701

    [15]

    Albert R, Barabási A L 2000 Phys. Rev. Lett. 85 5234

    [16]

    Newman M E J 2001 Phys. Rev. E 64 016132

    [17]

    Jeong H, Mason S P, Barabási A L, Oltvai Z N 2001 Nature 411 41

    [18]

    Fu F, Chen X J, Liu L H, Wang L 2007 arXiv: 0701323

    [19]

    Vázquez A, Weigt M 2003 Phys. Rev. E 67 027101

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计量
  • 文章访问数:  22549
  • PDF下载量:  10580
  • 被引次数: 0
出版历程
  • 收稿日期:  2010-07-23
  • 修回日期:  2010-09-08
  • 刊出日期:  2011-05-15

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