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Information diffusion under public crisis in BA scale-free network based on SEIR model-Taking COVID-19 as an example

机译:基于SEIR模型的BA尺度网络中公共危机的信息扩散为例

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摘要

In the view of the fact that online information in complex networks has an increasingly powerful impact on real society, an improved network public opinion diffusion model under public crisis is established in this paper. The model updates SEIR infectious disease model by using Mean Field Theory based on BA scale-free network, which presents scale-free characteristics as well as enhances the model accuracy and applicability. It conducts a sensitivity analysis and takes "2019-nCoV Explosion'' as a sample, crawling through related 180-day microblogs, forwards, comments and likes on Weibo. The results demonstrate that the propagation is greatly influenced by propagation probability, the network structure, the initial spreader and social effects, which contributes to the understanding of network public opinion diffusion and the control of the information dissemination direction. (C) 2021 Published by Elsevier B.V.
机译:鉴于复杂网络中的在线信息对现实社会的影响越来越大,本文建立了公共危机下改进的网络舆情扩散模型。该模型利用基于BA无标度网络的平均场理论对SEIR传染病模型进行了改进,使其具有无标度特性,提高了模型的精度和适用性。它进行敏感性分析,并采取以“2019年nCoV爆炸”为样本,在相关180天的微博上爬行、转发、评论和喜欢。结果表明,传播受传播概率、网络结构、初始传播者和社会效应的影响很大,这有助于理解网络舆情传播和控制信息传播离子方向。(c)2021由爱思唯尔B.V出版。

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