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Some Open Problem Sets for Generalized Blockmodeling

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Data Science and Classification

Abstract

This paper provides an introduction to the blockmodeling problem of how to cluster networks, based solely on the structural information contained in the relational ties, and a brief overview of generalized blockmodeling as an approach for solving this problem. Following a formal statement of the core of generalized blockmodeling, a listing of the advantages of adopting this approach to partitioning networks is provided. These advantages, together with some of the disadvantages of this approach, in its current state, form the basis for proposing some open problem sets for generalized blockmodeling. Providing solutions to these problem sets will transform generalized blockmodeling into an even more powerful approach for clustering networks of relations.

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Author information

Authors and Affiliations

  1. Department of Sociology, University of Pittsburgh, 2603 WWPH, Pittsburgh, PA, 15260, USA

    Patrick Doreian

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  1. Patrick Doreian
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Editor information

Editors and Affiliations

  1. Department of Mathematics, FMF, University of Ljubljana, Jadranska 19, 1000, Ljubljana, Slovenia

    Vladimir Batagelj

  2. Institute of Statistics, RWTH Aachen University, 52056, Aachen, Germany

    Hans-Hermann Bock

  3. Faculty of Social Sciences, University of Ljubljana, Kardeljeva pl. 5, 1000, Ljubljana, Slovenia

    Anuška Ferligoj  & Aleš Žiberna  & 

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Doreian, P. (2006). Some Open Problem Sets for Generalized Blockmodeling. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_14

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