Correlations in Networks associated to Preferential Growth

TL;DR

This paper investigates how different growth mechanisms influence network topology, revealing that preferential growth leads to hierarchical structures, while some real-world networks like yeast protein interactions do not exhibit such hierarchy.

Contribution

It demonstrates that preferential growth is not the primary factor in the development of certain real-world networks lacking hierarchical features.

Findings

Hierarchical topology emerges from combined random and preferential growth.

Real-world networks like yeast protein interactions lack hierarchical features.

Preferential growth may not be the main process in some scale-free networks.

Abstract

Combinations of random and preferential growth for both on-growing and stationary networks are studied and a hierarchical topology is observed. Thus for real world scale-free networks which do not exhibit hierarchical features preferential growth is probably not the main ingredient in the growth process. An example of such real world networks includes the protein-protein interaction network in yeast, which exhibits pronounced anti-hierarchical features.