Information communities: The network structure of communication

Peter Pal Zubcsek*, Imran Chowdhury, Zsolt Katona

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study puts forward a variable clique overlap model for identifying information communities, or potentially overlapping subgroups of network actors among whom reinforced independent links ensure efficient communication. We posit that the average intensity of communication between related individuals in information communities is greater than in other areas of the network. Empirical tests show that the variable clique overlap model is indeed more effective in identifying groups of individuals that have strong internal relationships in communication networks relative to prior cohesive subgroup models; the pathways generated by such an arrangement of connections are particularly robust against disruptions of information transmission. Our findings extend the scope of network closure effects proposed by other researchers working with communication networks using social network methods and approaches, a tradition which emphasizes ties between organizations, groups, individuals, and the external environment.

Original languageEnglish
Pages (from-to)50-62
Number of pages13
JournalSocial Networks
Volume38
Issue number1
DOIs
StatePublished - Jul 2014
Externally publishedYes

Keywords

  • Communication
  • Communities
  • Information transmission
  • Network closure

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