计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220100189-7.doi: 10.11896/jsjkx.220100189
王韩, 刘万平, 卢玲
WANG Han, LIU Wanping, LU Ling
摘要： 随着微博用户的迅速增长,对网络谣言的控制也变得更加重要。为了快速平息微博谣言,缩小谣言在微博网络上的传播范围,研究了影响谣言传播的关键因素。首先,结合谣言在微博网络上的传播场景,创新性地提出了UNFR传播模型。该模型将用户分为4类:未知者、中立者、转发者和反驳者,并考虑了衰减效应和遗忘机制,从而重新定义了模型节点状态转移。通过对模型的动力学分析及数值实验,分析了网络谣言传播规律。然后,在微博网络上进行传播模拟实验,验证了模型的合理性。通过分析模型参数对谣言传播的影响,得到了缩小谣言传播范围的方法。最后,研究了模型在不同参数初值下的谣言控制效果,并根据实验结果提出了有效的微博谣言控制策略。
中图分类号:
| [1]YAO Y,XIAO X,ZHANG C P,et al.Stability analysis of an SDILR model based on rumor recurrence on social media[J].Physica A:Statistical Mechanics and its Applications,2019,535:122236. [2]YU Z H,LU S,WANG D,et al.Modeling and analysis of rumor propagation in social networks[J].Information Sciences,2021,580:857-873. [3]YU S Z,YU Z Y,JIANG H J,et al.The dynamics and control of 2I2SR rumor spreading models in multilingual online social networks[J].Information Sciences,2021,581:18-41. [4]PAN Q H,LIU Y L,LU S Y,et al.Rumor spreading model considering the influence of public opinion environment[J].Journal of Physics:Conference Series,2020,1592:012089. [5]JIANG G Y,LI S P,LI M L.Dynamic rumor spreading of public opinion reversal on Weibo based on a two-stage SPNR model[J].Physica A:Statistical Mechanics and its Applications,2020,558:125005. [6]HUO L A,CHEN S J,ZHAO L J.Dynamic analysis of the rumor propagation model with consideration of the wise man and social reinforcement[J].Physica A:Statistical Mechanics and its Applications,2021,571:125828. [7]TIAN Y,DING X J.Rumor spreading model with considering debunking behavior in emergencies[J].Applied Mathematics and Computation,2019,363:124599. [8]LI R Q,LI Y W,MENG Z Y,et al.Rumor Spreading Model Considering Individual Activity and Refutation Mechanism Si-multaneously[J].IEEE Access,2020,8:63065-63076. [9]GAO L,LI R Q,SHU P P,et al.Effects of individual popularity on information spreading in complex networks[J].Physica A:Statistical Mechanics and its Applications,2018,489:32-39. [10]LIU W P,WU X,YANG W,et al.Modeling cyber rumor spreading over mobile social networks:A compartment approach[J].Applied Mathematics and Computation,2019,343:214-229. [11]LIU W P,ZHONG S M.Web malware spread modelling and optimal control strategies[J].Scientific Reports,2017,7:42308. [12]ZHU L H,ZHOU M T,LIU Y,et al.Nonlinear dynamic analysis and optimum control of reaction-diffusion rumor propagation models in both homogeneous and heterogeneous networks[J].Journal of Mathematical Analysis and Applications,2021,502(2):125260. [13]ZANETTE D H.Critical behavior of propagation on small-world networks[J].Physical Review E,Statistical,Nonlinear,and Soft Matter Physics,2001,64:050901. [14]MORENO Y,NEKOVEE M,PACHECO A F.Dynamics of Rumor Spreading in Complex Networks[J].Physical review.E,Statistical,nonlinear,and soft matter physics,2004,69:066130. [15]LI J R,JIANG H J,MEI X H,et al.Dynamical analysis of rumor spreading model in multi-lingual environment and heterogeneous complex networks[J].Information Sciences,2020,536:391-408. [16]ZHU L H,GUAN G.Dynamical analysis of a rumor spreading model with self-discrimination and time delay in complex networks[J].Physica A:Statistical Mechanics and its Applications,2019,533:121953. [17]LV L Y,CHEN D B,ZHOU T.The small world yields the most effective information spreading[J].New Journal of Physics,2011,13:123005. [18]EBBINGHAUS H.Memory:A Contribution to ExperimentalPsychology[J].Annals of Neurosciences,2013,20(4):155-156. [19]KERMACK W O,MCKENDRICK A G.A Contribution to the Mathematical Theory of Epidemics[J].Proceedings of The Royal Society A Mathematical Physical and EngineeringSciences,1927,115(772):700-721. [20]DRIESSCHE P,WATMOUGH J.Reproduction numbers andsub-threshold endemic equilibria for compartmental models of disease transmission[J].Mathematical Biosciences,2002,180(1/2):29-48. |
|
||
首页