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  3. Generalized Blockmodeling
  • Cited by 98
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    • Publisher:
      Cambridge University Press
      Publication date:
      January 2010
      November 2004
      ISBN:
      9780511584176
      9780521840859
      DOI:
      https://doi.org/10.1017/CBO9780511584176
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.76kg, 402 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Social Theory, Sociology: General Interest, Sociology
      Series:
      Structural Analysis in the Social Sciences (25)
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    Subjects:
    Social Theory, Sociology: General Interest, Sociology
    Series:
    Structural Analysis in the Social Sciences (25)
    Information

    Book description

    This book provides an integrated treatment of blockmodeling, the most frequently used technique in social network analysis. It secures its mathematical foundations and then generalizes blockmodeling for the analysis of many types of network structures. Examples are used throughout the text and include small group structures, little league baseball teams, intra-organizational networks, inter-organizational networks, baboon grooming networks, marriage ties of noble families, trust networks, signed networks, Supreme Court decisions, journal citation networks, and alliance networks. Also provided is an integrated treatment of algebraic and graph theoretic concepts for network analysis and a broad introduction to cluster analysis. These formal ideas are the foundations for the authors' proposal for direct optimizational approaches to blockmodeling which yield blockmodels that best fit the data, a measure of fit that is integral to the establishment of blockmodels, and creates the potential for many generalizations and a deductive use of blockmodeling.

    Reviews

    'This is a clearly presented and insightful book that provides an excellent mix of mathematical rigor and practical application. I would unhesitatingly recommend the book to anyone interested in social network analysis or discrete clustering methods.'

    Source: Journal of Classification

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