论文标题

异质性对超图触发模型的影响

The effect of heterogeneity on hypergraph contagion models

论文作者

Landry, Nicholas, Restrepo, Juan G.

论文摘要

网络社会传染过程(例如意见形成和流行传播)的动态通常是由多个节点之间的相互作用介导的。先前的结果表明,这些高阶相互作用可以深刻地改变传染过程的动力学,从而导致双重性,滞后和爆炸性过渡。在本文中,我们介绍并分析了高度图上的SIS模型动力学的高度平均场描述,即具有高阶相互作用的网络,并用HyperGraph的示例说明了它的适用性,其中传播均由两个链接(成对交互)和Triangles(三向相互作用)介导。我们考虑了各种链接和三角结构组织的模型,以及高阶传染和康复的不同机制。我们发现,当独立选择链接和三角形时,或与不相关的情况相比,链接分布和三角形连接正相关时,可以通过链路分布中的异质性,链接分布中的异质性来抑制爆炸性转变。我们通过微观模拟传播过程以及从平均场模型得出的分析预测来验证这些结果。我们的结果表明,高阶相互作用的结构可以对超图的传染过程产生重要影响。

The dynamics of network social contagion processes such as opinion formation and epidemic spreading are often mediated by interactions between multiple nodes. Previous results have shown that these higher-order interactions can profoundly modify the dynamics of contagion processes, resulting in bistability, hysteresis, and explosive transitions. In this paper, we present and analyze a hyperdegree-based mean-field description of the dynamics of the SIS model on hypergraphs, i.e. networks with higher-order interactions, and illustrate its applicability with the example of a hypergraph where contagion is mediated by both links (pairwise interactions) and triangles (three-way interactions). We consider various models for the organization of link and triangle structure, and different mechanisms of higher-order contagion and healing. We find that explosive transitions can be suppressed by heterogeneity in the link degree distribution, when links and triangles are chosen independently, or when link and triangle connections are positively correlated when compared to the uncorrelated case. We verify these results with microscopic simulations of the contagion process and with analytic predictions derived from the mean-field model. Our results show that the structure of higher-order interactions can have important effects on contagion processes on hypergraphs.

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