ISSN 0253-2778

CN 34-1054/N

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Open AccessOpen Access JUSTC Original Paper

An improved model for information dissemination and prediction on microblog networks

  • School of Computer and Control Engineering, Yantai University, Yantai 264005, China

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2014.07.007
  • Received Date: 21 March 2014
  • Accepted Date: 15 June 2014
  • Rev Recd Date: 15 June 2014
  • Publish Date: 30 July 2014
    Abstract

  • Abstract

    The rapid development of microblogging not only has led people into the We-Media era, but also creates favorable conditions for the rapid dissemination of information. Taking direct immunization into consideration, an improved SIR model was presented which uses differential equations to study the rules of information dissemination and to predict information on microblogs. The experiment result shows that the improved SIR model can effectively reflect the rules of information dissemination, and can predict microblog information dissemination more precisely than the microblog standard SIR model.

    Abstract

    The rapid development of microblogging not only has led people into the We-Media era, but also creates favorable conditions for the rapid dissemination of information. Taking direct immunization into consideration, an improved SIR model was presented which uses differential equations to study the rules of information dissemination and to predict information on microblogs. The experiment result shows that the improved SIR model can effectively reflect the rules of information dissemination, and can predict microblog information dissemination more precisely than the microblog standard SIR model.
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    • References(26)
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    [20]
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    [21]
    Zhou J, Liu Z H, Li B W. Influence of network structure on rumor propagation[J]. Physics Letters A, 2007, 368(6): 458-463.
    [22]
    Lü L, Chen D B, Zhou T. The small world yields the most effective information spreading[J]. New Journal of Physics, 2011, 13(12): 123005(1-10).
    [23]
    顾亦然, 夏玲玲. 在线社交网络中谣言的传播与抑制[J]. 物理学报, 2012, 61(23): 238701(1-7).
    [24]
    王辉,韩江洪,邓林,等.基于移动社交网络的谣言传播动力学研究[J].物理学报,2013,62(11):110505(1-12).
    [25]
    钱颖, 张楠, 赵来军, 等. 微博舆情传播规律研究[J]. 情报学报, 2012, 31(12): 1 299-1 304.
    [26]
    周涛,汪秉宏,韩筱璞,等.社会网络分析及其在舆情和疫情防控中的应用[J].系统工程学报,2010,25(6):742-754.
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    [1]
    Miller G. Social scientists wade into the tweet stream[J]. Science, 2011, 333(6051): 1 814-1 815.
    [2]
    Newman M E J, Forrest S, Balthrop J. Email networks and the spread of computer viruses[J]. Physical Review E, 2002, 66(3): 035101(1-4).
    [3]
    倪顺江, 翁文国, 范维澄. 具有局部结构的增长无标度网络中传染病传播机制研究[J]. 物理学报, 2009, 58(6): 3 707-3 713.
    [4]
    Moreno Y, Nekovee M, Pacheco A F. Dynamics of rumor spreading in complex networks[J]. Physical Review E, 2004, 69(6): 066130(1-8).
    [5]
    Zanette D H. Dynamics of rumor propagation on small-world networks[J]. Physical Review E, 2002, 65(4): 041908(1-9).
    [6]
    Yan G, Fu Z Q, Ren J, et al. Collective synchronization induced by epidemic dynamics on complex networks with communities[J]. Physical Review E, 2007, 75(1): 016108(1-5).
    [7]
    Zhao H, Gao Z Y. Modular effects on epidemic dynamics in small-world networks[J]. EuroPhysics Letters, 2007, 79(3): 38002(1-5).
    [8]
    仇慎伟, 王开, 刘茜, 等. 基于交通流量的病毒扩散动力学研究[J]. 物理学报, 2012, 61(15): 150201(1-7).
    [9]
    巩永旺, 宋玉蓉, 蒋国平. 移动环境下网络病毒传播模型及其稳定性研究[J]. 物理学报, 2012, 61(11): 110205(1-9).
    [10]
    鲁延玲, 蒋国平, 宋玉蓉. 自适应网络中病毒传播的稳定性和分岔行为研究[J]. 物理学报, 2013, 62(13): 130202(1-9).
    [11]
    李睿琪,唐明,许伯铭.多关系网络上的流行病传播动力学研究[J].物理学报,2013,62(16):168903(1-7).
    [12]
    王亚奇, 蒋国平. 复杂网络中考虑不完全免疫的病毒传播研究[J]. 物理学报, 2010, 59(10): 6 734-6 743.
    [13]
    Xia Chengyi, Liu Zhongxin, Chen Zengqiang, et al. Behavior of epidemic spreading with distributedinfection rate on complex networks[J]. Journal of University of Science and Technology of China, 2008, 38(12): 1 444-1 450.
    夏承遗,刘忠信,陈增强,等. 复杂网络上具有分布式传染速率的流行病传播行为[J].中国科学技术大学学报，2010,38(12): 1 444-1 450.
    [14]
    Sznajd-Weron K, Sznajd J. Opinion evolution in closed community[J]. International Journal of Modern Physics C, 2000, 11(6): 1 157-1 165.
    [15]
    Deffuant G, Amblard F, Weisbuch G, et al. How can extremism prevail? A study based on the relative agreement interaction model[EB/OL]. http://jasss.soc.surrey.ac.uk/5/4/1.html.
    [16]
    Hegselmann R, Krause U. Opinion dynamics and bounded confidence: Models, analysis, and simulation[J]. Journal of Artificial Societies and Social Simulation, 2002, 5(3): 1-24.
    [17]
    张彦超, 刘云, 张海峰, 等. 基于在线社交网络的信息传播模型[J]. 物理学报, 2011, 60(5): 050501(1-7).
    [18]
    Zhang Le, Zhong Qi, Li Zheng. The ISKS-ISK model of crisis information dissemination under time-varying communication rules[J]. Journal of University of Science and Technology of China, 2010, 40(9): 985-990.
    张乐, 钟琪, 李政. 时变传播规则下的危机信息ISKS-ISK两阶段传播模型及仿真[J]. 中国科学技术大学学报, 2010, 40(9): 985-990.
    [19]
    Liu Xionghong, Zhang Haifeng, Qin Xiaowei, et al. Research of rumor spreading on weighted short message networks[J]. Journal of University of Science and Technology of China, 2012, 42(5): 423-430.
    刘星宏, 张海峰, 秦晓卫, 等. 加权短信网络上的谣言传播行为研究[J]. 中国科学技术大学学报, 2012, 42(5): 423-430.
    [20]
    Sudbury A. The proportion of the population never hearing a rumour[J]. Journal of Applied Probability, 1985, 22(2): 443-446.
    [21]
    Zhou J, Liu Z H, Li B W. Influence of network structure on rumor propagation[J]. Physics Letters A, 2007, 368(6): 458-463.
    [22]
    Lü L, Chen D B, Zhou T. The small world yields the most effective information spreading[J]. New Journal of Physics, 2011, 13(12): 123005(1-10).
    [23]
    顾亦然, 夏玲玲. 在线社交网络中谣言的传播与抑制[J]. 物理学报, 2012, 61(23): 238701(1-7).
    [24]
    王辉,韩江洪,邓林,等.基于移动社交网络的谣言传播动力学研究[J].物理学报,2013,62(11):110505(1-12).
    [25]
    钱颖, 张楠, 赵来军, 等. 微博舆情传播规律研究[J]. 情报学报, 2012, 31(12): 1 299-1 304.
    [26]
    周涛,汪秉宏,韩筱璞,等.社会网络分析及其在舆情和疫情防控中的应用[J].系统工程学报,2010,25(6):742-754.
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