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Relating size and functionality in human social networks through complexity

  • B. J. West
  • , G. F. Massari
  • , G. Culbrethb
  • , R. Failla
  • , M. Bologna
  • , R. I.M. Dunbar
  • , P. Grigolini
  • United States Army Research Office
  • University of North Texas
  • University of Oxford

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

Extensive empirical evidence suggests that there is a maximal number of people with whom an individual can maintain stable social relationships (the Dunbar number). We argue that this arises as a consequence of a natural phase transition in the dynamic selforganization among N individuals within a social system. We present the calculated size dependence of the scaling properties of complex social network models to argue that this collective behavior is an enhanced form of collective intelligence. Direct calculation establishes that the complexity of social networks as measured by their scaling behavior is nonmonotonic, peaking around 150, thereby providing a theoretical basis for the value of the Dunbar number. Thus, we establish a theory-based bridge spanning the gap between sociology and psychology.

Original languageEnglish
Pages (from-to)18355-18358
Number of pages4
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number31
DOIs
StatePublished - 4 Aug 2020

Keywords

  • Allometry relation
  • Complexity
  • Dunbar number
  • Functionality/size
  • Network calculations

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