Factors determining nestedness in complex networks

TL;DR

This paper investigates the structural factors influencing network nestedness, revealing that degree heterogeneity and disassortativity significantly impact nestedness levels in complex networks.

Contribution

It introduces a refined nestedness measure and analyzes how basic network properties like degree distribution and assortativity affect nestedness.

Findings

Degree heterogeneity strongly influences nestedness.

Disassortativity correlates with higher nestedness.

Random disassortative networks tend to be naturally nested.

Abstract

Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure and go on to study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that heterogeneity in the degree has a very strong influence on nestedness. Once such an influence has been discounted, we find that nestedness is strongly correlated with disassortativity and hence, as random (neutral) networks have been recently found to be naturally disassortative, they tend to be naturally nested just as the result of chance.