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Multiobjective Blockmodeling for Social Network Analysis

Published online by Cambridge University Press:  01 January 2025

Michael Brusco ,
Patrick Doreian ,
Douglas Steinley  and
Cinthia B. Satornino
Michael Brusco*
Affiliation:
College of Business, Florida State University
Patrick Doreian
Affiliation:
Department of Sociology, University of Pittsburgh Faculty of Social Sciences, University of Ljubljana
Douglas Steinley
Affiliation:
Department of Psychological Sciences, University of Missouri, Columbia
Cinthia B. Satornino
Affiliation:
College of Business, Florida State University
*
Requests for reprints should be sent to Michael Brusco, College of Business, Florida State University, Tallahassee, FL 32306-1110, USA. E-mail: mbrusco@fsu.edu
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Abstract

To date, most methods for direct blockmodeling of social network data have focused on the optimization of a single objective function. However, there are a variety of social network applications where it is advantageous to consider two or more objectives simultaneously. These applications can broadly be placed into two categories: (1) simultaneous optimization of multiple criteria for fitting a blockmodel based on a single network matrix and (2) simultaneous optimization of multiple criteria for fitting a blockmodel based on two or more network matrices, where the matrices being fit can take the form of multiple indicators for an underlying relationship, or multiple matrices for a set of objects measured at two or more different points in time. A multiobjective tabu search procedure is proposed for estimating the set of Pareto efficient blockmodels. This procedure is used in three examples that demonstrate possible applications of the multiobjective blockmodeling paradigm.

Keywords

social networksblockmodelingmultiobjective programmingheuristicstabu search
Type
Original Paper
Information
Psychometrika , Volume 78 , Issue 3 , July 2013 , pp. 498 - 525
Copyright
Copyright © 2012 The Psychometric Society

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