English

Factors determining nestedness in complex networks

Physics and Society 2013-09-23 v2 Social and Information Networks Molecular Networks Neurons and Cognition

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.

Keywords

Cite

@article{arxiv.1307.4685,
  title  = {Factors determining nestedness in complex networks},
  author = {Samuel Johnson and Virginia Dominguez-Garcia and Miguel A. Munoz},
  journal= {arXiv preprint arXiv:1307.4685},
  year   = {2013}
}

Comments

7 pages, 4 figures

R2 v1 2026-06-22T00:53:12.314Z