Literature DB >> 15169201

Hierarchy measures in complex networks.

Ala Trusina1, Sergei Maslov, Petter Minnhagen, Kim Sneppen.   

Abstract

Using each node's degree as a proxy for its importance, the topological hierarchy of a complex network is introduced and quantified. We propose a simple dynamical process used to construct networks which are either maximally or minimally hierarchical. Comparison with these extremal cases as well as with random scale-free networks allows us to better understand hierarchical versus modular features in several real-life complex networks. For random scale-free topologies the extent of topological hierarchy is shown to smoothly decline with gamma, the exponent of a degree distribution, reaching its highest possible value for gamma</=2 and quickly approaching zero for gamma>3.

Year:  2004        PMID: 15169201     DOI: 10.1103/PhysRevLett.92.178702

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  27 in total

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9.  Graph hierarchy: a novel framework to analyse hierarchical structures in complex networks.

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