Multitype branching process method for modeling complex contagion on clustered networks

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Abstract

Complex contagion adoption dynamics are characterized by a node being more likely to adopt after multiple network neighbors have adopted. We show how to construct multitype branching processes to approximate complex contagion adoption dynamics on networks with clique-based clustering. This involves tracking the evolution of a cascade via different classes of clique motifs that account for the different numbers of active, inactive, and removed nodes. This discrete-time model assumes that active nodes become immediately and certainly removed in the next time step. This description allows for extensive Monte Carlo simulations (which are faster than network-based simulations), accurate analytical calculation of cascade sizes, determination of critical behavior, and other quantities of interest.

Original languageEnglish
Article number034306
JournalPhysical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
Volume105
Issue number3
DOIs
Publication statusPublished - Mar 2022

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