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

Authors :
Parés, Ferran
Garcia-Gasulla, Dario
Vilalta, Armand
Moreno, Jonatan
Ayguadé, Eduard
Labarta, Jesús
Cortés, Ulises
Suzumura, Toyotaro
Publication Year :
2017

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.<br />Comment: Accepted at the 6th International Conference on Complex Networks and Their Applications

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1703.09307
Document Type :
Working Paper