After establishing its mathematical foundations, this integrated study of blockmodeling, the most frequently used technique in social network analysis, generalizes blockmodeling for the examination of many network structures. It also includes a broad introduction to cluster analysis. The authors propose direct optimizational approaches to blockmodeling which yield blockmodels that best fit the data, and create the potential for many generalizations and a deductive use of blockmodeling.
After establishing its mathematical foundations, this integrated study of blockmodeling, the most frequently used technique in social network analysis, generalizes blockmodeling for the examination of many network structures. It also includes a broad introduction to cluster analysis. The authors propose direct optimizational approaches to blockmodeling which yield blockmodels that best fit the data, and create the potential for many generalizations and a deductive use of blockmodeling.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Patrick Doreian is a Professor of Sociology and Statistics at the University of Pittsburgh and is chair of the Department of Sociology. He has edited the Journal of Mathematical Sociology since 1982 and has been a member of the editorial board for Social Networks since 2003. He was a Centennial Professor at The London School of Economics during 2002. He has been a Visiting Professor at the University of California-Irvine and the University of Ljubljana. His interests include social networks, mathematical sociology, interorganizational networks, environmental sociology and social movements.
Inhaltsangabe
Preface 1. Social networks and blockmodels 2. Network data sets 3. Mathematical prelude 4. Relations and graphs for network analysis 5. Clustering approaches 6. An optimizational approach to conventional blockmodeling 7. Foundations for generalized blockmodeling 8. Blockmodeling two-mode network data 9. Semirings and lattices 10. Balance theory and blockmodeling signed networks 11. Symmetric-acyclic blockmodels 12. Extending generalized blockmodeling Bibliography Author index Subject index.
Preface 1. Social networks and blockmodels 2. Network data sets 3. Mathematical prelude 4. Relations and graphs for network analysis 5. Clustering approaches 6. An optimizational approach to conventional blockmodeling 7. Foundations for generalized blockmodeling 8. Blockmodeling two-mode network data 9. Semirings and lattices 10. Balance theory and blockmodeling signed networks 11. Symmetric-acyclic blockmodels 12. Extending generalized blockmodeling Bibliography Author index Subject index.
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