Please wait a minute...
文章检索
复杂系统与复杂性科学  2016, Vol. 13 Issue (2): 83-89    DOI: 10.13306/j.1672-3813.2016.02.010
  本期目录 | 过刊浏览 | 高级检索 |
面向网络论坛的谣言传播与抑制研究
徐会杰, 蔡皖东, 陈桂茸
西北工业大学计算机学院,西安 710129
Research on Web Forum Oriented Rumors Spreading and Inhibitions
XU Huijie, CAI Wandong, CHEN Guirong
School of Computer Science and Technology, Northwestern Polytechnical University, Xi′an 710129, China
全文: PDF(1040 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 基于网络论坛中用户行为的异质性和病毒传播的SEIR模型,提出了面向网络论坛的SEIR谣言传播模型。首先根据模型在非均匀网络中的平均场方程,推导网络论坛中谣言传播的临界阈值,表明在谣言传播率有限的情况下,增加用户间的信任机制可以有效抑制谣言在网络中的传播;然后通过仿真与数值分析,验证模型的有效性以及信任机制的引入能够有效降低谣言的影响力、传播速率和影响范围;最后结合仿真与数值分析的结论和网络论坛用户间的高影响力有限信任关系,给出了抑制谣言传播的高影响力用户免疫策略。实验结果表明,该策略与传统的免疫策略相比能够取得更好的谣言抑制效果。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
徐会杰
蔡皖东
陈桂茸
关键词 网络论坛谣言传播SEIR模型非均匀网络信任机制高影响力用户免疫    
Abstract:A rumor spreading model for the web forum based on the heterogeneity of web forum user behaviors and SEIR model is proposed in this paper. First, according to the mean-field equations of the model on inhomogeneous networks, the critical threshold of the spreading of rumor is deduced, the result of theoretical analysis shows that the increase in trust mechanism between users can effectively inhibit the rumor spread in the network with limited velocity of propagation; Then the simulation and numerical analysis of the model itself and the influences of trust mechanism to the model is given, which verify the validity of the model and the introduction of trust mechanism can effectively reduce the rumor influence, the velocity of rumor spreading and the rumor size; Finally, combined with the previous conclusions and the high-influence limited trust relationships between web forum users, a high-influence immunization strategy is given. The experimental results show that the strategy able to reach better effect than traditional immunization strategy.
Key wordsweb forum    rumor spreading    SEIR model    inhomogeneous network    trust mechanism    high-influence immunization
收稿日期: 2014-04-06      出版日期: 2025-02-25
ZTFLH:  TP393  
作者简介: 徐会杰(1989-),男,河南漯河人,讲师,博士研究生,主要研究方向为网络信息安全与信息对抗。
引用本文:   
徐会杰, 蔡皖东, 陈桂茸. 面向网络论坛的谣言传播与抑制研究[J]. 复杂系统与复杂性科学, 2016, 13(2): 83-89.
XU Huijie, CAI Wandong, CHEN Guirong. Research on Web Forum Oriented Rumors Spreading and Inhibitions[J]. Complex Systems and Complexity Science, 2016, 13(2): 83-89.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2016.02.010      或      https://fzkx.qdu.edu.cn/CN/Y2016/V13/I2/83
[1] 霍良安. 突发事件发生后不实信息的传播问题研究[D].上海:上海交通大学, 2012.
Huo Liangan. Research on the spread of unconfirmed information after the emergency occurs[D].Shanghai:Shanghai Jiao Tong University, 2012.
[2] 王辉. 在线社交网络上谣言传播关键问题研究[D].合肥:合肥工业大学, 2013.
Wang Hui. Rumor propagation in online social networks[D].Hefei: Hefei University of Technology,2013.
[3] 刘瑞生.年终盘点:微传播时代的网络谣言特征与应对策略[EB/OL].[2013-12-30].http://society.people.com.cn/n/2013/1230/c229589-23976960.html.
[4] Zanette D H. Dynamics of rumor propagation on small world networks[J].Physical Review E, 2002, 65(4): 041908.
[5] Nekovee M, Moreno Y, Bianconi G. Theory of rumor spreading in complex social networks[J].Physcia A,2007, 374(8): 457-470.
[6] Zhou J, Liu Z, Li B W. Influence of network structure on rumor propagation[J].Physical Letters A, 2007,368(6): 458-463.
[7] Kesten H, Sidoravicius V. The spreading of a rumor or infection in a moving population[J].Annals of Probability, 2005,33(6): 2402-2462.
[8] 潘灶烽, 汪小帆, 李翔. 可变聚类系数无标度网络上的谣言传播仿真研究[J].系统仿真学报,2006,18(8): 2346-2348.
Pan Zaofeng, Wang Xiaofan, Li Xiang. Simulation investigation on rumor spreading on scale-free network with tunable clustering[J].Journal of System Simulation, 2006, 18(8): 2346-2348.
[9] 刘常昱, 胡晓峰, 司光亚, 等. 舆论涌现模型研究[J].复杂系统与复杂性科学, 2007,4(1): 4-27.
Liu Changyu, Hu Xiaofeng, Si Guangya, et al. Study on the consensus emergency model[J].Complex Systems and Complexity Science, 2007,4(1): 4-27.
[10] 朱恒民, 刘凯, 卢子芳. 媒体作用下互联网舆情话题传播模型研究[J].现代图书情报技术, 2013, 29(3): 45-50.
Zhu Hengmin, Liu Kai, Lu Zifang. Study on topic propagation model of internet public opinion under the influence of the media[J].New Technology of Library and Information Service, 2013, 29(3): 45-50.
[11] Wang Y Q, Yang X Y, Han Y L, et al. Rumor spreading model with trust mechanism in complex social networks[J].Commun Theor Phys, 2013, 59(4): 510-516.
[12] 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): 544-550.
Gu Yiran, Xia Lingling. The propagation and inhibition of online social network[J].Chinese Journal of Physics, 2012, 61(23): 544-550.
[13] Aron J L, Schwartz I B. Seasonality and period-doubling bifurcations in an epidemic model[J].Journal of Theoretical Biology, 1984, 110(4): 665-679.
[14] 司夏萌, 刘云. 虚拟社区中人际交互行为的统计分析研究[J].物理学报, 2011, 60(7): 859-866.
Si Xiameng, Liu Yun. Empirical analysisof interpersonal interacting behavior invirtual community[J].Chinese Journal of Physics, 2011, 60(7): 859-866.
[15] 陈桂茸, 蔡皖东, 徐会杰, 等. 网络舆论演化的高影响力优先有限信任模型[J].上海交通大学学报, 2013, 47(1): 155-160.
Chen Guirong, Cai Wandong, Xu Huijie, et al. High-effect priority bounded confidence model for network opinion evolution[J].Journal of ShangHai Jiao Tong University, 2013, 47(1): 155-160.
[16] Xiong F, Liu Y. Empirical analysis and modeling of users′ topic interests in online forums[J].PloS One, 2012, 7(12): e50912.
[17] Yu J, Hu Y, Yu M, et al. Analyzing netizens’ view and reply behaviors on the forum[J].Physica A: Statistical Mechanics and its Applications, 2010, 389(16): 3267-3273.
[18] Ding F, Liu Y, Shen B, et al. An evolutionary game theory model of binary opinion formation[J].Physica A: Statistical Mechanics and its Applications, 2010, 389(8): 1745-1752.
[19] Takeuchi Y, Ma W, Beretta E. Global asymptotic properties of a delay SIR epidemic model with finite incubation times[J].Nonlinear Analysis: Theory, Methods & Applications, 2000, 42(6): 931-947.
[20] 徐会杰, 蔡皖东, 王剑平, 等. 基于时间变化图的网络论坛意见领袖识别算法[J].计算机科学, 2012, 39(8): 51-54.
Xu huijie, Cai Wandong, Wang Jianping, et al. Identifying algorithm for opinion leaders of forums based on time-varying graphs[J].Computer Science, 2012, 39(8): 51-54.
[1] 高天, 许小可. 基于社团结构的抑制校园新冠传播研究[J]. 复杂系统与复杂性科学, 2024, 21(3): 9-16.
[2] 王志平, 王佳. 基于超网络的舆论演化动态模型[J]. 复杂系统与复杂性科学, 2021, 18(2): 29-38.
[3] 赵子鸣, 勾文沙, 高晓惠, 陈清华. COVID-19疫情防控需要社区监测及接触者追踪并重[J]. 复杂系统与复杂性科学, 2020, 17(4): 1-8.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed