Models and methods in social network analysis
Author(s)
Bibliographic Information
Models and methods in social network analysis
(Structural analysis in the social sciences, 27)
Cambridge University Press, 2005
- : hard
- : pbk
Available at / 70 libraries
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Doshisha University Library (Imadegawa)
: hard301.6||C9502086700961,
: pbk301.6||C9502106100093 -
Library, Institute of Developing Economies, Japan External Trade Organization図
: pbkG||30||M616694556
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Note
Includes bibliographies and index
Description and Table of Contents
Description
Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
Table of Contents
- Acknowledgements
- 1. Introduction Stanley Wasserman, John Scott and Peter J. Carrington
- 2. Recent developments in network measurement Peter V. Marsden
- 3. Network sampling and model fitting Ove Frank
- 4. Extending centrality Martin Everett and Stephen P. Borgatti
- 5. Positional analyses of sociometric data Patrick Doreian, Vladimir Batagelj and Anuska Ferligoj
- 6. Network models and methods for studying the diffusion of innovations Thomas W. Valente
- 7. Using correspondence analysis for joint displays of affiliation networks Katherine Faust
- 8. An introduction to random graphs, dependence graphs, and p* Stanley Wasserman and Garry Robins
- 9. Random graph models for social networks: multiple relations or multiple raters Laura M. Koehly and Philippa Pattison
- 10. Interdependencies and social processes: dependence graphs and generalized dependence structures Garry Robins and Philippa Pattison
- 11. Models for longitudinal network data Tom A. B. Snijders
- 12. Graphical techniques for exploring social network data Linton C. Freeman
- 13. Software for social network analysis Mark Huisman and Marijtje A. J. van Duijn
- Index.
by "Nielsen BookData"