Coevolution and correlated multiplexity in multiplex networks

Jung Y eol Kim, K. I. Goh

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)58702
Number of pages1
JournalPhysical Review Letters
Volume111
Issue number5
Publication statusPublished - 2013 Aug 2

Fingerprint

Growth
complex systems
cascades
magnetic permeability
interactions

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Coevolution and correlated multiplexity in multiplex networks. / Kim, Jung Y eol; Goh, K. I.

In: Physical Review Letters, Vol. 111, No. 5, 02.08.2013, p. 58702.

Research output: Contribution to journalArticle

@article{c08c3f0b599d474c9d58702319feefd1,
title = "Coevolution and correlated multiplexity in multiplex networks",
abstract = "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.",
author = "Kim, {Jung Y eol} and Goh, {K. I.}",
year = "2013",
month = "8",
day = "2",
language = "English",
volume = "111",
pages = "58702",
journal = "Physical Review Letters",
issn = "0031-9007",
publisher = "American Physical Society",
number = "5",

}

TY - JOUR

T1 - Coevolution and correlated multiplexity in multiplex networks

AU - Kim, Jung Y eol

AU - Goh, K. I.

PY - 2013/8/2

Y1 - 2013/8/2

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84925032310&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84925032310&partnerID=8YFLogxK

M3 - Article

C2 - 23952454

VL - 111

SP - 58702

JO - Physical Review Letters

JF - Physical Review Letters

SN - 0031-9007

IS - 5

ER -