Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (11): 3409-3414.DOI: 10.11772/j.issn.1001-9081.2019040739

• Frontier & interdisciplinary applications • Previous Articles    

Rumor propagation model based on edge-based compartmental theory

LUO Jingyu, TANG Ningjiu   

  1. College of Computer Science, Sichuan University, Chengdu Sichuan 610065, China
  • Received:2019-04-29 Revised:2019-07-10 Online:2019-08-21 Published:2019-11-10

基于边划分理论的谣言传播模型

罗靖宇, 唐宁九   

  1. 四川大学 计算机学院, 成都 610065
  • 通讯作者: 唐宁九
  • 作者简介:罗靖宇(1995-),男,四川成都人,硕士研究生,主要研究方向:复杂网络、机器学习;唐宁九(1960-),男,四川成都人,教授,博士,主要研究方向:软件工程、复杂系统。

Abstract: Aiming at the problem that spreader nodes will be influenced by their neighbors during the recovery in the rumor propagation process, a rumor propagation model based on edge-based compartmental theory was proposed. Firstly, a set of dynamic equations were established using the improved edge-based compartmental theory, and the propagation range and breaking threshold were theoretically analyzed. Then the influence of factors including network structure, propagation probability and basic recovery probability were analyzed through numerical simulation. Finally, an effective immunization strategy to control rumor propagation range and breaking threshold was presented on the above basis. The results of theoretical analysis and numerical simulation show that, compared with the classical SIR (Susceptible-Infected-Recovered) rumor propagation model, the presented model decrease the period of rumor propagation and increase the peak of the propagation of spreader nodes slightly. Through comparison experiments with the random immunization strategy, in the proposed strategy the edges with higher product of the degrees of two nodes were immuned preferentially to obtain better effect when rumor has minor propagation probability, and the edges with lower product of the degrees of two nodes were immuned preferentially to obtain better effect when rumor has larger propagation probability. Study results indicate that the presented model conform to the characteristics of rumor fading away phase and can provide theoretical and numerical support for rumor prediction and control.

Key words: complex network, Susceptible-Infected-Recovered (SIR) model, rumor propagation, edge-based compartmental theory, immunization strategy

摘要: 针对谣言传播过程中传播态节点恢复时会受其邻居节点状态影响的问题,提出了一种基于边划分理论的谣言传播模型。首先,使用改进的边划分理论建立起谣言传播的动力学方程组,推演出谣言在复杂网络上的传播范围值和爆发阈值;然后,通过数值仿真实验研究网络结构、传播概率和基础恢复概率等参数对谣言传播的影响;在此基础之上,提出了可以有效控制谣言传播范围和爆发阈值的免疫策略。理论分析和仿真结果表明,与经典的SIR模型相比,提出的谣言传播模型缩短了谣言传播的周期,传播态节点比例的峰值则有小幅提高。对比实验发现,与现有的随机免疫策略相比,当谣言的传播概率较大时,优先免疫连接小度节点的边能得到更小的谣言传播范围;反之,当谣言的传播概率较小时,优先免疫连接大度节点的边可以有更小的谣言传播范围。研究结果表明,提出的谣言传播模型符合谣言消退期的特征,为谣言传播的预测与控制提供了理论和数值上的支持。

关键词: 复杂网络, 易感态-感染态-恢复态模型, 谣言传播, 边划分理论, 免疫策略

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