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社交网络中基于贝叶斯和半环代数模型的节点影响力计算机理

赵佳 喻莉 李静茹

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社交网络中基于贝叶斯和半环代数模型的节点影响力计算机理

赵佳, 喻莉, 李静茹

Node influence calculation mechanism based on Bayesian and semiring algebraic model in social networks

Zhao Jia, Yu Li, Li Jing-Ru
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  • 本文综合考虑网络结构及节点间的互动等关键因素, 提出了一种节点影响力分布式计算机理. 首先根据节点交互行为在时域上的自相似特性, 运用带折扣因子的贝叶斯模型计算节点间的直接影响力; 然后运用半环模型来分析节点间接影响力的聚合; 最后根据社交网络的小世界性质及传播门限, 综上计算出节点的综合影响力. 仿真结果表明, 本文给出的模型能有效抑制虚假粉丝导致的节点影响力波动, 消除了虚假粉丝的出现对节点影响力计算带来的干扰, 从中选择影响力高的若干节点作为传播源节点, 可以将信息传播到更多数目的节点, 促进了信息在社交网络中的传播.
    In social networks, many applications and spreading depend on the nodes with high influence to do viral marketing, which indicates that nodes' influence should be measured in a comprehensive and reasonable way. The appearance of fake fans results in change of network topology and brings new challenge to topology-based traditional methods. This paper incorporates both the network topology and interactions among nodes into our new distribution mechanism of node influence calculation in social networks. Considering the similarity of node behaviors in time domain and several key factors, this paper presents by a discounted Bayesian model for direct influence between nodes at first. Then a semi-ring-based aggregation implements for indirect influence and the composite influence are obtained by the combination of both direct and indirect influences. Simulation shows that this mechanism not only performs well against fake fans attack and restrains the fluctuation of nodes' influence, but also spreads to more nodes when we choose several nodes with high influence under our method to be source nodes.
    • 基金项目: 国家自然科学基金重点项目(批准号: 61231010, 60972016)和湖北省杰出青年科学家基金(批准号: 2009CDA150)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 61231010, 60972016), and the Funds of Distinguished Young Scientists (Grant No. 2009CDA150).
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    Guimera R, Danon L, Diaz-Guilera A, Giralt F, Arenas A 2003 Phys. Rev. E 68 065103

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  • [1]

    Carmen Camarero, Rebeca San José 2011 Computers in Human Behavior 27 2292

    [2]

    Eytan Bakshy, Jake M Hofman, Winter A Mason, Duncan J Watts 2011 Proceedings of the fourth ACM international conference on Web search and data mining p65

    [3]

    Mursel Tasgin, Haluk O Bingol 2012 Advs. Complex Syst. 15 1250061

    [4]

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

    [5]

    Zhou J Y, Zhang Y L, Cheng J 2011 the 6th International Conference on Frontier of Computer Science and Technology (FCST-11) p1512

    [6]

    Newman M E J 2003 SIAM Review 45 167

    [7]

    Page L, Brin S, Motwani R, Winograd T 1999 Technical Report Stanford InfoLab 1999–66

    [8]

    L L Y, Zhang Y C, Yeung C H, Zhou T 2011 PLoS ONE 6 e21202

    [9]

    Ilyas M U, Shafip M Z, Liu A X, Radha H 2011 Infocom p561

    [10]

    Theodorakopoulos G, Baras J S 2006 IEEE Journal on Selected Areas in Communications 24 318

    [11]

    Lars Backstrom, Paolo Boldiy, Marco Rosay, Johan Ugander, Sebastiano Vigna, 2011 arXiv: 1111.4570

    [12]

    Watts D J, Strogatz S H 1998 Nature 393 440

    [13]

    Albert-László Barabásí, Réka Albert 1999 Science 286 509

    [14]

    Wang X F, Li X, Chen G R 2012 Network Science: An Introduction (1st Edn.) (Beijing: Higher Education Press) (in Chinese) [汪小帆, 李翔, 陈关荣 2012 网络科学导论 (北京: 高等教育出版社)]

    [15]

    Guo J L, Wang L N 2007 Acta Phys. Sin. 56 5635 (in Chinese) [郭进利, 汪丽娜 2007 物理学报 56 5635]

    [16]

    Opsahl T, Panzarasa P 2009 Social Networks 31 155

    [17]

    Newman M E J 2006 Phys. Rev. E 74 036104

    [18]

    Guimera R, Danon L, Diaz-Guilera A, Giralt F, Arenas A 2003 Phys. Rev. E 68 065103

    [19]

    Watts D J 2001 Proceedings of the National Academy of Science of the United States of America 99 5766

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出版历程
  • 收稿日期:  2013-01-05
  • 修回日期:  2013-03-19
  • 刊出日期:  2013-07-05

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