Hierarchy Measures in Complex 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 γ -- the exponent of a degree distribution -- reaching its highest possible value for γ ≤ 2 and quickly approaching zero for γ>3.

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