Why are so many networks disassortative?

Samuel Johnson*, Joaquín J. Torres, J. Marro, Miguel A. Muñoz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A wide range of empirical networks - whether biological, technological, information-related or linguistic - generically exhibit important degree-degree anticorrelations (i.e., they are disassortative), the only exceptions being social ones, which tend to be positively correlated (assortative). Using an information-theory approach, we show that the equilibrium state of highly heterogeneous (scale-free) random networks is disassortative. This not only gives a parsimonious explanation to a long-standing question, but also provides a neutral model against which to compare experimental data and ascertain whether a given system is being driven from equilibrium by correlating mechanisms.

Original languageEnglish
Title of host publicationNon-Equilibrium Statistical Physics Today - Proceedings of the 11th Granada Seminar on Computational and Statistical Physics
Pages249-250
Number of pages2
DOIs
Publication statusPublished - 2011
Event11th Granada Seminar on Computational and Statistical Physics - La Herradura, Spain
Duration: 13 Sept 201017 Sept 2010

Publication series

NameAIP Conference Proceedings
Volume1332
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference11th Granada Seminar on Computational and Statistical Physics
Country/TerritorySpain
CityLa Herradura
Period13/09/1017/09/10

Keywords

  • assortativity
  • correlated networks
  • Random graphs
  • Shannon entropy

ASJC Scopus subject areas

  • General Physics and Astronomy

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