Self-similar community structure in a network of human interactions

Roger Guimerà; León Danon; Albert Dı́az-Guilera; Francesc Giralt; Àlex Arenas

doi:10.1103/physreve.68.065103

Abstract

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Keywords

Complex networkSelf-organizationComputer scienceScalingComplex systemMechanism (biology)Human dynamicsCommunity structureNetwork structureEvolving networksState (computer science)Network formationInformation flowInformation networksData scienceTheoretical computer scienceArtificial intelligenceKnowledge managementWorld Wide WebMathematicsEpistemologyAlgorithm

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Publication Info

Year: 2003
Type: article
Volume: 68
Issue: 6
Pages: 065103-065103
Citations: 1477
Access: Closed

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APA Style

                            
                                
                                    Roger Guimerà, 
                                
                                    León Danon, 
                                
                                    Albert Dı́az-Guilera
                                
                                et al.
                            
                            (2003). 
                            Self-similar community structure in a network of human interactions. 
                            Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
                            , 68
                            (6)
                            , 065103-065103.
                            https://doi.org/10.1103/physreve.68.065103
                        

Identifiers

DOI: 10.1103/physreve.68.065103