Asymmetric inter-layer interactions induce a double transition of information spreading

Yang, Zheng; Wu, Jiao; He, Jiaxu; Xu, Kesheng; Zheng, Muhua

doi:10.1016/j.chaos.2023.113487

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…The study of epidemic on the multiplex network has developed more than ten years and many interesting results have been found in [12][13][14]. The multiplex network related to awareness has attracted much attention in the study of epidemic spreading [4,[15][16][17][18][19]. Considering the interrelation between epidemic spreading and social awareness, Funk et al [20] added a sensitivity coefficient related to individual awareness to SIR model, and this method leads to a reduction in the outbreak scale but does not affect the threshold.…”

Section: Introductionmentioning

confidence: 99%

Epidemic spreading on coupling network with higher-order information layer

Zhu,

Li,

2023

New J. Phys.

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Epidemic tends to break out with information spreading which occurs between pairwise individuals or in groups. In active social online platform, three or more individuals can share information or exchange opinion, which could be modeled as a clique beyond pairwise interaction. This work studies the influence of information with higher-order cliques whose closure probability is described by higher-order clustering coefficient on epidemic spreading. The coupled spreading process of disease and awareness follows an unaware-aware-unaware-susceptible-infected-susceptible (UAU-SIS) model on multiplex networks. We deduce the epidemic threshold of multiplex network with higher-order cliques, and explore the effects of cliques on epidemic spreading process at slow, middle and fast pairwise information spreading rates. The results show that the epidemic threshold and higher-order clustering coefficient are positively correlated. Moreover, we find that the effect of higher-order cliques could be ignored when pairwise information spreading rate is large enough. Finally, we show that the steady infection ratio decreases with the increase of the higher-order clustering coefficient.

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