Skip to content
Register Sign in Wishlist
Generalized Blockmodeling

Generalized Blockmodeling

$87.99 (C)

Part of Structural Analysis in the Social Sciences

  • Date Published: November 2004
  • availability: Available
  • format: Hardback
  • isbn: 9780521840859

$ 87.99 (C)
Hardback

Add to cart Add to wishlist

Other available formats:
eBook


Looking for an examination copy?

This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • 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.

    • Completely general and very flexible treatment of blockmodeling
    • Actual blockmodels established fit the data better than those using alternative approaches
    • By emphasizing the specification of blockmodels in terms of block types there is the potential for continuous generalizations and the analyses of many different types of networks
    Read more

    Reviews & endorsements

    '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.' Journal of Classification

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity

    ×

    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?

    ×

    Product details

    • Date Published: November 2004
    • format: Hardback
    • isbn: 9780521840859
    • length: 402 pages
    • dimensions: 229 x 152 x 27 mm
    • weight: 0.76kg
    • contains: 103 b/w illus. 117 tables
    • availability: Available
  • Table of Contents

    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.

  • Authors

    Patrick Doreian, University of Pittsburgh
    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, University of Ljubljana
    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.

    Anuska Ferligoj, University of Ljubljana
    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).

Related Books

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×
warning icon

Turn stock notifications on?

You must be signed in to your Cambridge account to turn product stock notifications on or off.

Sign in Create a Cambridge account arrow icon
×

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.

Cancel

Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

×
Please fill in the required fields in your feedback submission.
×