Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm

TL;DR

Fluid Communities is a scalable, efficient community detection algorithm inspired by fluid interactions, capable of identifying a variable number of communities with high accuracy and diversity in large networks.

Contribution

It introduces the first propagation-based community detection algorithm that can identify a variable number of communities with high efficiency and diversity.

Findings

Achieves near state-of-the-art accuracy on synthetic graphs

Capable of detecting a variable number of communities

Finds communities significantly different from other methods

Abstract

We introduce a community detection algorithm (Fluid Communities) based on the idea of fluids interacting in an environment, expanding and contracting as a result of that interaction. Fluid Communities is based on the propagation methodology, which represents the state-of-the-art in terms of computational cost and scalability. While being highly efficient, Fluid Communities is able to find communities in synthetic graphs with an accuracy close to the current best alternatives. Additionally, Fluid Communities is the first propagation-based algorithm capable of identifying a variable number of communities in network. To illustrate the relevance of the algorithm, we evaluate the diversity of the communities found by Fluid Communities, and find them to be significantly different from the ones found by alternative methods.