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Dynamical Analysis of an SE2IR Information Propagation Model in Social Networks
Discrete Dynamics in Nature and Society ( IF 1.4 ) Pub Date : 2021-06-22 , DOI: 10.1155/2021/5615096
Qian Zhang 1 , Xianyong Li 1 , Yajun Du 1 , Jian Zhu 2
Affiliation  

Due to the inequality of users’ (nodes’) status and the influence of external forces in the progress of the information propagation in a social network, the infected nodes hold different levels of propagation capacity. For this reason, the infected nodes are classified into two categories: the high influential infected nodes and the ordinary influential infected nodes which separately account for 20% and 80% by Pareto’s principle. By borrowing the SEIR epidemic model, this paper proposes an SE2IR information propagation model. Meanwhile, the global asymptotical stabilities of the spread-free equilibrium point and local spread equilibrium point are proved for this model. This paper also puts forward a series of information control strategies including perceived values of users, social reinforcement intensity, and information timeliness in the social network. Through simulation experiments without or with control strategies on a real company e-mail network dataset, this paper verifies the stability and correctness of the model and the feasibility and effectiveness of the control strategies in the information propagation process, presenting that the model is closer to the real process of the information propagation in the social network.

中文翻译:

社交网络中 SE2IR 信息传播模型的动态分析

由于用户(节点)身份的不平等以及社交网络中信息传播过程中外力的影响,被感染的节点具有不同程度的传播能力。为此,将感染节点分为两类:高影响力感染节点和普通有影响力感染节点,按照帕累托原理分别占20%和80%。本文借用SEIR流行病模型,提出了一种SE2IR信息传播模型。同时,证明了该模型的无利差平衡点和局部利差平衡点的全局渐近稳定性。本文还提出了一系列信息控制策略,包括用户感知价值、社会强化强度、以及社交网络中的信息及时性。通过在真实的公司电子邮件网络数据集上进行无控制策略或有控制策略的仿真实验,验证了模型的稳定性和正确性以及控制策略在信息传播过程中的可行性和有效性,表明该模型更接近于信息在社交网络中传播的真实过程。
更新日期:2021-06-22
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