Generalized communities in networks

TL;DR

This paper introduces a broad extension of community detection in networks, capturing diverse structural patterns beyond traditional communities, and provides a method for identifying these structures in real-world data.

Contribution

It presents a novel, principled approach for detecting generalized network structures that include but are not limited to communities, enhancing understanding of network shapes.

Findings

Demonstrates the method on real-world networks

Reveals new insights into network structures

Extends community detection to broader patterns

Abstract

A substantial volume of research has been devoted to studies of community structure in networks, but communities are not the only possible form of large-scale network structure. Here we describe a broad extension of community structure that encompasses traditional communities but includes a wide range of generalized structural patterns as well. We describe a principled method for detecting this generalized structure in empirical network data and demonstrate with real-world examples how it can be used to learn new things about the shape and meaning of networks.