Identifying networks with common organizational principles

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Abstract

Many complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet it remains challenging to accurately cluster networks that are of a different size and density, but hypothesized to be structurally similar. In this article, we address this problem by introducing a new network comparison methodology that is aimed at identifying common organizational principles in networks. The methodology is simple, intuitive and applicable in a wide variety of settings ranging from the functional classification of proteins to tracking the evolution of a world trade network.

Bibliographical metadata

Original languageEnglish
Pages (from-to)887-913
JournalJournal of Complex Networks
Volume6
Issue number6
Early online date3 Feb 2018
DOIs
Publication statusPublished - 3 Feb 2018

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