Scaling of nestedness in complex networks

TL;DR

This paper investigates the scaling properties of nestedness in complex networks, revealing how heterogeneity and node type fractions influence nestedness patterns using a graph-theoretic approach.

Contribution

It provides a quantitative analysis of nestedness scaling in model networks, highlighting the effects of connectivity heterogeneity and node type composition.

Findings

Heterogeneous connectivity enhances nestedness.

Nestedness depends on the fraction of node types.

Scaling behavior varies with network structure.

Abstract

Nestedness characterizes the linkage pattern of networked systems, indicating the likelihood that a node is linked to the nodes linked to the nodes with larger degrees than it. Networks of mutualistic relationship between distinct groups of species in ecological communities exhibit such nestedness, which is known to support the network robustness. Despite such importance, quantitative characteristics of nestedness is little understood. Here we take graph-theoretic approach to derive the scaling properties of nestedness in various model networks. Our results show how the heterogeneous connectivity patterns enhance nestedness. Also we find that the nestedness of bipartite networks depend sensitively on the fraction of different types of nodes, causing nestedness to scale differently for nodes of different types.