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Stochastic model of rumor propagation dynamics on homogeneous social network with expert interaction and fluctuations in contact transmissions

机译:具有专家交互与联系传输中的互联网传播动力学的随机模型

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摘要

The study of uncertainty and its effect on information diffusion have become a recent problem in social network analysis. Contact rates between the social network users are not constant. There exist uncertainty in user's interest due to incomplete knowledge about others and stochastic properties present in user behavior. Keeping given this fact, we introduce a rumor model in a homogeneously mixed population on a social network including expert intervention. We also studied the stochastic version of the proposed model including fluctuations in contact rates. We ascertained a threshold known as basic influence number, R-0 and R-0 for deterministic and stochastic model respectively. We acquired the condition of local and global asymptotic stability of rumor free equilibrium respectively for the deterministic and stochastic model. Moreover, the mathematical state of epidemic invasion was obtained for the stochastic version of the model. Here, we conclude that epidemic can still grow in the presence of fluctuations (R-0 1) even when there is no epidemic invasion in the deterministic case (R-0 1). So a diffusion rate can be a cause of transient epidemic advance. (C) 2018 Elsevier B.V. All rights reserved.
机译:对不确定性的研究及其对信息扩散的影响已成为社会网络分析的最新问题。社交网络用户之间的联系率并不常态。由于关于用户行为中存在的其他人和随机性质的不完整知识,用户兴趣的不确定性。掌握这一事实,我们在一个在包括专家干预的社交网络上介绍了一个狂热的混合群体中的谣言模型。我们还研究了所提出的模型的随机版,包括接触率的波动。我们确定了一种称为基本影响号,R-0和R-0的阈值,分别用于确定性和随机模型。我们在确定性和随机模型中分别获得了谣言自由平衡的局部和全球渐近稳定性的条件。此外,为模型的随机版本获得了流行病的数学状态。在这里,我们得出结论,即使在确定性情况下没有流行病侵袭(R-0 <1),疫情仍然可以在波动的存在下生长(R-0& 1)。因此,扩散速度可能是瞬态流行性进步的原因。 (c)2018年elestvier b.v.保留所有权利。

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