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- W4387132313 abstract "In complex social systems encoded as hypergraphs, higher-order (i.e., group) interactions taking place among more than two individuals are represented by hyperedges. One of the higher-order correlation structures native to hypergraphs is the nestedness: Some hyperedges can be entirely contained (that is, nested) within another larger hyperedge, which itself can also be nested further in a hierarchical manner. Yet the effect of such hierarchical structure of hyperedges on the dynamics has remained unexplored. In this context, here we propose a random nested-hypergraph model with a tunable level of nestedness and investigate the effects of nestedness on a higher-order susceptible-infected-susceptible process. By developing an analytic framework called the facet approximation, we obtain the steady-state fraction of infected nodes on the random nested-hypergraph model more accurately than existing methods. Our results show that the hyperedge-nestedness affects the phase diagram significantly. Monte Carlo simulations support the analytical results." @default.
- W4387132313 created "2023-09-29" @default.
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- W4387132313 date "2023-09-28" @default.
- W4387132313 modified "2023-10-18" @default.
- W4387132313 title "Contagion dynamics on hypergraphs with nested hyperedges" @default.
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- W4387132313 doi "https://doi.org/10.1103/physreve.108.034313" @default.
- W4387132313 hasPublicationYear "2023" @default.
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