Modeling Valued Organizational Communication Networks Using Exponential Random Graph Models

Andrew Pilny, Yannick Atouba

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

For years, organizational communication scholars have been interested in the mechanisms that influence the formation of communication networks. One way to gain a deeper insight into the factors that shape such networks is to model them using exponential random graph modeling (ERGM). However, ERGM has only been applicable to binary networks, reducing communication to something that is either present or not. This article illustrates valued ERGM for organizational communication networks that have a weight associated with each tie. Using a data set on friendship strength between collaborative scientists, results show there are important differences when the network is modeled as binary versus when modeled as valued. In particular, the valued model showed that scientists are more selective regarding friendship (less outdegree activity). Moreover, there were several differences regarding how popular certain disciplines were over others. An online appendix with the R code and data is also included.

Original languageEnglish
Pages (from-to)250-264
Number of pages15
JournalManagement Communication Quarterly
Volume32
Issue number2
DOIs
StatePublished - May 1 2018

Bibliographical note

Publisher Copyright:
© 2017, © The Author(s) 2017.

Keywords

  • communication
  • network analysis
  • research methods
  • social network

ASJC Scopus subject areas

  • Communication
  • Strategy and Management

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