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Generalized Blockmodeling by Patrick Doreian
Book DescriptionThis 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.
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Book DetailsISBN: 9780521840859
(228mm x 152mm x 27mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 8-Nov-2004
Country of Publication: United Kingdom
Books By Author Patrick Doreian
Understanding Large Temporal Networks and Spatial Networks, Hardback (October 2014)
A comprehensive, sweeping work by an acclaimed team of authors at the forefront of this hot topic, Understanding Large Temporal Networks and Spatial Networks explores the different approaches to studying large temporal and spatial networks and links them to computationally sound models of changing structure to detect patterns.
Problem of Solidarity, Hardback (October 1998)View all books by Patrick Doreian
In this text the authors examine how solidarity is produced and reproduced, how it is related to social processes, and how such processes can be formalized and create conditions for productively studying their properties.
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Author Biography - Patrick Doreian
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. Vladimir Batagelj is a Professor of Discrete and Computational Mathematics at the University of Ljubljana and is chair of the Department of Theoretical Computer Science at IMFM, Ljubljana. He is a member of editorial boards of Informatica and Journal of Social Structure. He was visiting professor at University of Pittsburgh in 1990 to 1991 and at University of Konstanz (Germany) in 2002. His main research interests are in graph theory, algorithms on graphs and networks, combinatorial optimization, data analysis and applications of information technology in education. He is coauthor (with Andrej Mrvar) of Pajek - a program for analysis and visualization of large networks. Anu ka Ferligoj is a Professor of Statistics at the University of Ljubljana and is dean of the Faculty of Social Sciences. She is editor of the series Metodoloski zvezki since 1987 and is a member of the editorial boards of the Journal of Mathematical Sociology, Journal of Classification, Social Networks, and Statistics in Transition. She was a Fulbright scholar in 1990 and Visiting Professor at the University of Pittsburgh. She was awarded the title of Ambassador of Science of the Republic of Slovenia in 1997. Her interests include multivariate analysis (constrained and multicriteria clustering), social networks (measurement quality and blockmodeling), and survey methodology (reliability and validity of measurement).
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