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Home List of Titles Exponential random graph models for social networks: theories, methods and applications
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/216516
- Exponential random graph models for social networks: theories, methods and applications
- Lusher, Dean; Koskinen, Johan; Robins, Garry
- Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal, and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages, and interpret the results.
- Publication type
- Structural analysis in the social sciences, no. 35
- Publication year
- Exponential random graph models; Social network analysis; Social network theory; Social science
- Cambridge University Press
- 9780521141383, 0521141389
- Publisher URL
- Copyright © 2013.
- Peer reviewed