Optimizational Approach to Blockmodeling

Anuska Ferligoj, Patrick Doreian, Vladimir Batagelj

Abstract


The goal of blockmodeling is to reduce a large, potentially incoherent network to a smaller comprehensible structure that can be interpreted more readily. Blockmodeling, as an empirical procedure, is based on the idea that units in a network can be grouped according to the extent to which they are equivalent, under some meaningful definition of equivalence. In the paper an optimizational approach to blockmodeling is discussed. Methods where a set of observed relations are fitted to a pre-specified blockmodel are also presented.


Keywords


Social network analysis, relations, local optimization, clustering

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