Distinct channels of interaction in a complex networked system define network layers, which coexist and cooperate for the system's function. Towards understanding such multiplex systems, we propose a modeling framework based on coevolution of network layers, with a class of minimalistic growing network models as working examples. We examine how the entangled growth of coevolving layers can shape the network structure and show analytically and numerically that the coevolution can induce strong degree correlations across layers, as well as modulate degree distributions. We further show that such a coevolution-induced correlated multiplexity can alter the system's response to the dynamical process, exemplified by the suppressed susceptibility to a social cascade process.
ASJC Scopus subject areas
- General Physics and Astronomy