Journal Article

FZJ-2015-03401

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Clustering drives assortativity and community structure in ensembles of networks

Foster, D. V. (Corresponding Author) ; Foster, J. G. ; Grassberger, P.FZJ* ; Paczuski, M.

2011
APS College Park, Md.

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Please use a persistent id in citations: http://hdl.handle.net/2128/8733  doi:10.1103/PhysRevE.84.066117

Abstract: Clustering, assortativity, and communities are key features of complex networks. We probe dependencies between these features and find that ensembles of networks with high clustering display both high assortativity by degree and prominent community structure, while ensembles with high assortativity show much less enhancement of the clustering or community structure. Further, clustering can amplify a small homophilic bias for trait assortativity in network ensembles. This marked asymmetry suggests that transitivity could play a larger role than homophily in determining the structure of many complex networks.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)
2. John von Neumann - Institut für Computing (NIC)

Research Program(s):

1. 411 - Computational Science and Mathematical Methods (POF2-411) (POF2-411)

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Database coverage:
; ; ; Current Contents - Physical, Chemical and Earth Sciences ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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