期刊文献+

一种基于耦合网络的RD-IHSAT网络谣言传播模型

A model of RD-IHSAT rumor dissemination based on coupling network
下载PDF
导出
摘要 为探究谣言在社交网络中的传播规律,基于耦合原理,构建由巴拉巴西-阿尔伯特(Barabási-Albert,BA)无标度网络与瓦茨-斯特罗加茨(Watts-Strogatz,WS)小世界网络组成的沉默者、辟谣者、无知者、犹豫者、传谣者、铁杆传谣者、疲惫者(reticent,debunker,ignorant,hesitated,spreader,adherent,tired,RD-IHSAT)谣言传播模型。该模型在易感者、感染者、移出者(susceptible,infective,removal,SIR)模型的基础上引入兴趣衰弱机制、感知社会共识机制、沉默与反沉默的螺旋等因素,并融入犹豫者、铁杆传谣者、沉默者、辟谣者等角色,使其更加逼近真实情形。仿真结果显示,耦合网络极大地促进了谣言的传播,不仅加快谣言爆发速度,而且扩大谣言传播规模;提高对犹豫者的辟谣概率能够极为显著地抑制谣言规模,是控制谣言传播的最有力因素;仅降低谣言传播率对谣言控制作用较小;提高沉默群体的比例是遏制谣言传播的关键一环;对辟谣时滞的把控极大地影响了辟谣效果。 To explore the spread of rumors in social network,based on the principles of coupling network,the model of RD-IHSAT was established on Barabási-Albert(BA)scale free network and Watts-Strogatz(WS)small world network.The classic model of SIR was optimized,by combining it with three concerns,the interest decay,the social consensus and the spiral of silence effect,and adding four roles,hesitated,adherent,reticent and debunker.Results of numerical simulations are as follows:an information outbreak can be triggered by coupling network,not only the spreading speed but the scale as well;the dissemination can be markedly suppressed when the probability of ru-mor-refuting for the hesitated and spreaders arises;the chances of transition from spreaders to adherents drop;in-creasing the proportion of silent groups is a key part of curbing the spread of rumors;the control of the time lag in refuting rumors will greatly affect the effect of refuting rumors.
作者 韩一士 徐雨欣 卢甜甜 HAN Yishi;XU Yuxin;LU Tiantian(Zhejiang Police College,Hangzhou 310053,China)
机构地区 浙江警察学院
出处 《电信科学》 2023年第2期118-131,共14页 Telecommunications Science
关键词 谣言传播 耦合网络 兴趣衰弱 社会共识 沉默的螺旋 RD-IHSAT模型 rumor dissemination coupling network interest decay social consensus spiral of silence model of RD-IHSAT
  • 相关文献

参考文献9

二级参考文献117

  • 1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. 被引量:86
  • 2汪小帆,李翔,陈关荣.网络科学导论[M].北京:高等教育出版社,2012.
  • 3王众托.系统工程引论(第4版)[M].北京:电子工业出版社,2014.
  • 4Newman M. E. Spread of Epidemic Disease on Networks[ J]. Physical Review E, 2002,66(1) :016128.
  • 5Moreno Y., Nekovee M., Pacheco A. F. Dynamics of Rumor Spreading in Complex Networks [ J]. Physical Review E, 2004, 69(6) :066130.
  • 6Xiong F., Liu Y., Zhang Z., et al. An Information Diffusion Model Based on Retweeting Mechanism for Online Social Media[ J ]. Physics Letters A, 2012,376(30) :2103-2108.
  • 7Centola D. The Spread of Behavior in an Online Social Network Experiment [ J ]. Science, 2010,329(5996) :1194-1197.
  • 8Lu L. Y., Chen D. B., Zhou T. The Small World Yields the Most Effective Information Spreading[ J]. New Journal of Physics, 2011,13(12) : 123005.
  • 9Santos F. C., Rodrigues J. F., Pacheco J. M. Epidemic Spreading and Cooperation Dynamics on Homogene-ons Small-World Net- works [ J ]. Physical Review E, 2005,72 ( 5 ) : 056128.
  • 10Zhao K., Stehle J., Bianconi G., et al. Social Network Dynamics of Face-to-Face Interactions [ J]. Physical Review E, 2011, 83(5) :056109.

共引文献112

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部