Detecting Fuzzy Community Structures in Complex Networks with a Potts Model

Jörg Reichardt and Stefan Bornholdt
Phys. Rev. Lett. 93, 218701 – Published 15 November 2004

Abstract

A fast community detection algorithm based on a q-state Potts model is presented. Communities (groups of densely interconnected nodes that are only loosely connected to the rest of the network) are found to coincide with the domains of equal spin value in the minima of a modified Potts spin glass Hamiltonian. Comparing global and local minima of the Hamiltonian allows for the detection of overlapping (“fuzzy”) communities and quantifying the association of nodes with multiple communities as well as the robustness of a community. No prior knowledge of the number of communities has to be assumed.

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  • Received 12 February 2004

DOI:https://doi.org/10.1103/PhysRevLett.93.218701

©2004 American Physical Society

Authors & Affiliations

Jörg Reichardt* and Stefan Bornholdt*

  • Interdisciplinary Center for Bioinformatics, University of Leipzig, Kreuzstrasse 7b, D-04103 Leipzig, Germany

  • *Present address: Institute for Theoretical Physics, University of Bremen, D-28359 Bremen, Germany.

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Issue

Vol. 93, Iss. 21 — 19 November 2004

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