Communities in Networks

TL;DR

This paper provides a comprehensive survey of community detection in networks, covering concepts, methods, applications, and open problems, highlighting its interdisciplinary relevance and connections to physics and optimization.

Contribution

It offers a structured overview of community detection techniques, methodologies, and open challenges, serving as a guide for newcomers and researchers in the field.

Findings

Summarizes key community detection methods.

Identifies open problems and future directions.

Connects community detection to physics and optimization.

Abstract

We survey some of the concepts, methods, and applications of community detection, which has become an increasingly important area of network science. To help ease newcomers into the field, we provide a guide to available methodology and open problems, and discuss why scientists from diverse backgrounds are interested in these problems. As a running theme, we emphasize the connections of community detection to problems in statistical physics and computational optimization.