The architecture of complex weighted networks

TL;DR

This paper investigates the structure of complex weighted networks, introducing new metrics to analyze the heterogeneity and correlations of weights and topology in social and infrastructure systems.

Contribution

It develops novel metrics for weighted networks, enabling the first analysis of correlations between weights and topology in real-world systems.

Findings

Weighted networks show significant heterogeneity in connection strengths.

Correlations between weights and topology reveal hierarchical organization.

New metrics effectively characterize complex network structures.

Abstract

Networked structures arise in a wide array of different contexts such as technological and transportation infrastructures, social phenomena, and biological systems. These highly interconnected systems have recently been the focus of a great deal of attention that has uncovered and characterized their topological complexity. Along with a complex topological structure, real networks display a large heterogeneity in the capacity and intensity of the connections. These features, however, have mainly not been considered in past studies where links are usually represented as binary states, i.e. either present or absent. Here, we study the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively. In both cases it is possible to assign to each edge of the graph a weight proportional to the intensity or capacity of the connections among the various elements of the network. We define new appropriate metrics combining weighted and topological observables that enable us to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices. This information allows us to investigate for the first time the correlations among weighted quantities and the underlying topological structure of the network. These results provide a better description of the hierarchies and organizational principles at the basis of the architecture of weighted networks.