Assessing the relevance of node features for network structure

TL;DR

This paper introduces an entropy-based indicator to quantify how much node features influence network structure, demonstrated on social, biological, and transportation networks, providing complementary insights to existing measures.

Contribution

The paper proposes a novel entropy-based measure to assess the relevance of node features for network structure, applicable across various types of networks.

Findings

The measure effectively quantifies feature dependence in social, biological, and transportation networks.

It provides additional insights beyond traditional network analysis metrics.

The method is versatile and can be applied to different network domains.

Abstract

Networks describe a variety of interacting complex systems in social science, biology and information technology. Usually the nodes of real networks are identified not only by their connections but also by some other characteristics. Examples of characteristics of nodes can be age, gender or nationality of a person in a social network, the abundance of proteins in the cell taking part in a protein-interaction networks or the geographical position of airports that are connected by directed flights. Integrating the information on the connections of each node with the information about its characteristics is crucial to discriminating between the essential and negligible characteristics of nodes for the structure of the network. In this paper we propose a general indicator, based on entropy measures, to quantify the dependence of a network's structure on a given set of features. We apply this method to social networks of friendships in US schools, to the protein-interaction network of Saccharomyces cerevisiae and to the US airport network, showing that the proposed measure provides information which complements other known measures.