Multiobjective Blockmodeling for Social Network Analysis

✍ Scribed by Michael Brusco, Patrick Doreian, Douglas Steinley, Cinthia B. Satornino

• Book ID: 120791112
• Publisher: Springer
• Year: 2012
• Tongue: English
• Weight: 640 KB
• Volume: 78
• Category: Article
• ISSN: 0033-3123
• DOI: 10.1007/s11336-012-9313-1

✦ Synopsis

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.