Detecting fuzzy community structures in complex networks with a Potts model.

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.

• Publication year

  2004

• Venue

  Physical Review Letters

• Publication date

  2004-02-12

• Fields of study

  Medicine, Physics, Computer Science

• Identifiers
  DOI 10.1103/PhysRevLett.93.218701arXiv cond-mat/0402349PMID 15601068
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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