Network analysis of 2-mode data

Stephen P. Borgatti, Martin G. Everett

Research output: Contribution to journalArticlepeer-review

729 Scopus citations

Abstract

Network analysis is distinguished from traditional social science by the dyadic nature of the standard data set. Whereas in traditional social science we study monadic attributes of individuals, in network analysis we study dyadic attributes of pairs of individuals. These dyadic attributes (e.g. social relations) may be represented in matrix form by a square 1-mode matrix. In contrast, the data in traditional social science are represented as 2-mode matrices. However, network analysis is not completely divorced from traditional social science, and often has occasion to collect and analyze 2-mode matrices. Furthermore, some of the methods developed in network analysis have uses in analysing non-network data. This paper presents and discusses ways of applying and interpreting traditional network analytic techniques to 2-mode data, as well as developing new techniques. Three areas are covered in detail: displaying 2-mode data as networks, detecting clusters and measuring centrality.

Original languageEnglish
Pages (from-to)243-269
Number of pages27
JournalSocial Networks
Volume19
Issue number3
DOIs
StatePublished - Aug 1997

Keywords

  • Centrality
  • Clusters
  • Networks

ASJC Scopus subject areas

  • Anthropology
  • Sociology and Political Science
  • General Social Sciences
  • General Psychology

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