Hierarchy Measures in Complex Networks
Soft Condensed Matter
2008-06-24 v2 Molecular Networks
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 -- the exponent of a degree distribution -- reaching its highest possible value for and quickly approaching zero for .
Cite
@article{arxiv.cond-mat/0308339,
title = {Hierarchy Measures in Complex Networks},
author = {Ala Trusina and Sergei Maslov and Petter Minnhagen and Kim Sneppen},
journal= {arXiv preprint arXiv:cond-mat/0308339},
year = {2008}
}
Comments
4 pages, 4 figures