搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

考虑谣言清除过程的网络谣言传播与抑制

万贻平 张东戈 任清辉

引用本文:
Citation:

考虑谣言清除过程的网络谣言传播与抑制

万贻平, 张东戈, 任清辉

Propagation and inhibition of online rumor with considering rumor elimination process

Wan Yi-Ping, Zhang Dong-Ge, Ren Qing-Hui
PDF
导出引用
  • 网络谣言传播是网络传播动力学的重要课题之一. 网络谣言传播常常同时混杂谣言感染和谣言清除两个过程, 对这一现象的分析可以帮助我们更好地认识社会网络中的信息传播. 本文在susceptible-infective-refractory谣言传播模型的基础上增加谣言清除者, 定义了谣言感染和谣言清除的规则, 提出SIERsEs谣言传播模型, 建立了模型的平均场方程, 从理论上分析了谣言传播的稳态, 并求解出谣言传播的感染阈值和清除阈值. 仿真计算分析了感染和清除过程同时作用时, 感染率、清除率和网络平均度对谣言传播的影响. 研究发现, 网络平均度过小或过大, 谣言传播稳定后的影响力都将处于低水平. 分析了目标免疫和熟人免疫等传统免疫策略的不足, 针对网络环境下谣言抑制的特点, 提出主动免疫和被动免疫两种网络谣言免疫策略, 并研究了传播者遗忘率、清除者遗忘率和开始免疫时间参数对这两种谣言免疫策略有效性的影响. 需要重视的是: 研究发现一些直观看来有效的谣言抑制措施反而可能提高谣言的影响力. 研究结果有助于深化对于网络传播动力学的理解, 同时为发展有效的网络谣言抑制策略提供新的思路.
    As one of the most important aspects of spreading dynamics on networks, propagation of rumor, which includes the process of rumor diffusing and elimination, plays an important role in the understanding of information dissemination within social networks. However, the current understanding of rumor propagation within networks is far from clear, especially the full analysis of the process of rumor diffusing and elimination is lacking. Here, with the rumor elimination process supplemented to the susceptible-infective-refractory (SIR) rumor spreading model, a modified rumor spreading model is established and defined as spreader-ignorant-eliminater-Rstifler-Estifler (SIERsEs) model. The developed mean-field equations of SIERsEs model, with the diffussing and elimination thresholds calculated, could describe the theory of steady-state dynamics of the rumor propagation. Simulation analysis is performed to assess the interaction between the diffussing and elimination process, and estimate the influences of diffusing rate, estimation rate, and averaged degree of the network, on the rumor spreading. The results show whether low or high value of average network degree would accompany a low level of the influence of rumor propagation. In addition, the shortcomings of the traditional immunization strategies, such as targeted immunization and acquaintances immunization, are pointed out. Based on this understanding, we propose two optimized immunization strategies, defined as active immunization and passive immunization, and we further evaluate how different parameters (forgetting rate of spreader, forgetting rate of eliminater and the starting time of immunization) affect the suppression effectiveness of the newly developed active and passive immunization strategies. Importantly, some so-called rumor-inhibition strategies actually could not inhibit but enhance the rumor propagation instead. These obtained findings in the present study could not only elaborate our understandings in spreading dynamics within network, but also provide an insight into the developing effective strategies of inhibiting rumor propagation.
      通信作者: 张东戈, sys_analysis@126.com
    • 基金项目: 国家自然科学基金(批准号: 61174198)资助的课题.
      Corresponding author: Zhang Dong-Ge, sys_analysis@126.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61174198).
    [1]

    Daley D J, Kendall D G 1965 J. Appl. Math. 1 42

    [2]

    Maki D P, Thompson M 1973 Mathematical Models and Applications (New Jersey: Englewood Cliffs) p10

    [3]

    Zanette D H 2001 Phys. Rev. E 64 050901

    [4]

    Zanette D H 2002 Phys. Rev. E 65 041908

    [5]

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

    [6]

    Xing Q B, Zhang Y B, Liang Z N 2011 Chin. Phys. B 20 120201

    [7]

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

    [8]

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

    [9]

    Trpevski D, Tang W K S, Kocarev L 2010 Phys. Rev. E 81 056102

    [10]

    Zhao L J, Wang Q, Cheng J J, Chen Y C, Wang J J, Huang W 2011 Physica A: Statist. Mech. Appl. 390 2619

    [11]

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

    [12]

    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 63 180501]

    [13]

    Zan Y, Wu J, Li P, Yu Q 2014 Physica A: Statist. Mech. Appl. 405 159

    [14]

    Wang J, Zhao L, Huang R 2014 Physica A: Statist. Mech. Appl. 398 43

    [15]

    Allport G W, Postman L 1947 Public Opin. Quart. 10 501

    [16]

    Peterson W, Gist N 1951 Am. J. Sociol. 57 159

    [17]

    Rasnow R L 1988 J. Commun. 38 1

    [18]

    Pendleton S C 1998 Lang. Commun. 1 69

    [19]

    Karrer B, Newman M E J 2011 Phys. Rev. E 84 036106

    [20]

    Wang W, Tang M, Yang H, Do Y, Lai Y C, Lee G 2014 Sci. Rep. 4 5097

    [21]

    Huang J Y, Jin X G 2011 J. Syst. Sci. Compl. 24 449

    [22]

    Singh A, Singh Y N 2013 Acta Phys. Pol. B 44 5

    [23]

    Albert R, Jeong H, Barabási A L 2000 Nature 406 378

    [24]

    Cohen R, Erez K, Ben-Avraham D, Havlin S 2000 Phys. Rev. Lett. 85 4626

    [25]

    Pastor-Satorras R, Vespignani A 2001 Phys. Rev. Lett. 86 3200

    [26]

    Gómez-Gardenes J, Echenique P, Moreno Y 2006 Eur. Phys. J. B 49 259

    [27]

    Cohen R, Havlin S, Ben-Avraham D 2003 Phys. Rev. Lett. 91 247901

    [28]

    Wang W, Tang M, Zhang H F, Gao H, Do Y, Liu Z H 2014 Phys. Rev. E 90 042803

    [29]

    Anderson R M, May R M 1992 Infectious Diseases in Humans (Oxford: Oxford University Press) pp530-540

  • [1]

    Daley D J, Kendall D G 1965 J. Appl. Math. 1 42

    [2]

    Maki D P, Thompson M 1973 Mathematical Models and Applications (New Jersey: Englewood Cliffs) p10

    [3]

    Zanette D H 2001 Phys. Rev. E 64 050901

    [4]

    Zanette D H 2002 Phys. Rev. E 65 041908

    [5]

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

    [6]

    Xing Q B, Zhang Y B, Liang Z N 2011 Chin. Phys. B 20 120201

    [7]

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

    [8]

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

    [9]

    Trpevski D, Tang W K S, Kocarev L 2010 Phys. Rev. E 81 056102

    [10]

    Zhao L J, Wang Q, Cheng J J, Chen Y C, Wang J J, Huang W 2011 Physica A: Statist. Mech. Appl. 390 2619

    [11]

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

    [12]

    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 63 180501]

    [13]

    Zan Y, Wu J, Li P, Yu Q 2014 Physica A: Statist. Mech. Appl. 405 159

    [14]

    Wang J, Zhao L, Huang R 2014 Physica A: Statist. Mech. Appl. 398 43

    [15]

    Allport G W, Postman L 1947 Public Opin. Quart. 10 501

    [16]

    Peterson W, Gist N 1951 Am. J. Sociol. 57 159

    [17]

    Rasnow R L 1988 J. Commun. 38 1

    [18]

    Pendleton S C 1998 Lang. Commun. 1 69

    [19]

    Karrer B, Newman M E J 2011 Phys. Rev. E 84 036106

    [20]

    Wang W, Tang M, Yang H, Do Y, Lai Y C, Lee G 2014 Sci. Rep. 4 5097

    [21]

    Huang J Y, Jin X G 2011 J. Syst. Sci. Compl. 24 449

    [22]

    Singh A, Singh Y N 2013 Acta Phys. Pol. B 44 5

    [23]

    Albert R, Jeong H, Barabási A L 2000 Nature 406 378

    [24]

    Cohen R, Erez K, Ben-Avraham D, Havlin S 2000 Phys. Rev. Lett. 85 4626

    [25]

    Pastor-Satorras R, Vespignani A 2001 Phys. Rev. Lett. 86 3200

    [26]

    Gómez-Gardenes J, Echenique P, Moreno Y 2006 Eur. Phys. J. B 49 259

    [27]

    Cohen R, Havlin S, Ben-Avraham D 2003 Phys. Rev. Lett. 91 247901

    [28]

    Wang W, Tang M, Zhang H F, Gao H, Do Y, Liu Z H 2014 Phys. Rev. E 90 042803

    [29]

    Anderson R M, May R M 1992 Infectious Diseases in Humans (Oxford: Oxford University Press) pp530-540

  • [1] 王楠, 肖敏, 蒋海军, 黄霞. 时滞和扩散影响下社交网络谣言传播动力学.  , 2022, 71(18): 180201. doi: 10.7498/aps.71.20220726
    [2] 王祁月, 刘润然, 贾春晓. 复杂网络上的意见动力学对谣言传播的影响.  , 2021, 70(6): 068902. doi: 10.7498/aps.70.20201486
    [3] 孙皓宸, 刘肖凡, 许小可, 吴晔. 基于连续感染模型的新冠肺炎校园传播与防控策略分析.  , 2020, 69(24): 240201. doi: 10.7498/aps.69.20201106
    [4] 朱霖河, 李玲. 基于辟谣机制的时滞谣言传播模型的动力学分析.  , 2020, 69(2): 020501. doi: 10.7498/aps.69.20191503
    [5] 张菊平, 郭昊明, 荆文君, 靳祯. 基于真实信息传播者的谣言传播模型的动力学分析.  , 2019, 68(15): 150501. doi: 10.7498/aps.68.20190191
    [6] 王亚奇, 王静, 杨海滨. 基于复杂网络理论的微博用户关系网络演化模型研究.  , 2014, 63(20): 208902. doi: 10.7498/aps.63.208902
    [7] 胡兆龙, 刘建国, 任卓明. 基于节点度信息的自愿免疫模型研究.  , 2013, 62(21): 218901. doi: 10.7498/aps.62.218901
    [8] 黄斌, 赵翔宇, 齐凯, 唐明, 都永海. 复杂网络的顶点着色及其在疾病免疫中的应用.  , 2013, 62(21): 218902. doi: 10.7498/aps.62.218902
    [9] 王辉, 韩江洪, 邓林, 程克勤. 基于移动社交网络的谣言传播动力学研究.  , 2013, 62(11): 110505. doi: 10.7498/aps.62.110505
    [10] 柴争义, 陈亮, 朱思峰. 混沌免疫多目标算法求解认知引擎参数优化问题.  , 2012, 61(5): 058801. doi: 10.7498/aps.61.058801
    [11] 吕天阳, 朴秀峰, 谢文艳, 黄少滨. 基于传播免疫的复杂网络可控性研究.  , 2012, 61(17): 170512. doi: 10.7498/aps.61.170512
    [12] 王亚奇, 杨晓元. 一种无线传感器网络簇间拓扑演化模型及其免疫研究.  , 2012, 61(9): 090202. doi: 10.7498/aps.61.090202
    [13] 顾亦然, 夏玲玲. 在线社交网络中谣言的传播与抑制.  , 2012, 61(23): 238701. doi: 10.7498/aps.61.238701
    [14] 刘朝华, 张英杰, 章兢, 吴建辉. 基于免疫双态微粒群的混沌系统自抗扰控制.  , 2011, 60(1): 019501. doi: 10.7498/aps.60.019501
    [15] 王亚奇, 蒋国平. 考虑网络流量的无标度网络病毒免疫策略研究.  , 2011, 60(6): 060202. doi: 10.7498/aps.60.060202
    [16] 周杰, 俎云霄. 一种用于认知无线电资源分配的并行免疫遗传算法.  , 2010, 59(10): 7508-7515. doi: 10.7498/aps.59.7508
    [17] 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.  , 2010, 59(10): 6734-6743. doi: 10.7498/aps.59.6734
    [18] 别梦杰, 钟伟荣, 陈弟虎, 李立, 邵元智. 关联白噪声对抗肿瘤体系免疫效果的影响.  , 2009, 58(1): 97-101. doi: 10.7498/aps.58.97
    [19] 奚衍斌, 张 宇, 王晓钢, 刘 悦, 余 虹, 姜东光. 调制磁场清除柱形等离子体发生器中的尘埃颗粒.  , 2005, 54(1): 164-172. doi: 10.7498/aps.54.164
    [20] 郭元恒. B—A型电离真空计内电清除现象的探讨.  , 1961, 17(3): 157-162. doi: 10.7498/aps.17.157
计量
  • 文章访问数:  7953
  • PDF下载量:  366
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-08-17
  • 修回日期:  2015-09-10
  • 刊出日期:  2015-12-05

/

返回文章
返回
Baidu
map