Borgatti, Stephen P. and Everett, Martin G. (1997) Network analysis of 2-mode data. Social Networks, 19 (3). pp. 243-269. ISSN 0378-8733 (doi:https://doi.org/10.1016/S0378-8733(96)00301-2)

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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.

Item Type:	Article
Uncontrolled Keywords:	networks, clusters, centrality
Subjects:	Q Science > QA Mathematics
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Business
Related URLs:	Publisher
Last Modified:	14 Oct 2016 09:00
URI:	http://gala.gre.ac.uk/id/eprint/378

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