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Statistical Models for Social Networks

Abstract:

Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For single networks, the older literature concentrated on conditionally uniform models. Various types of latent space models have been developed: for discrete, general metric, ultrametric, Euclidean, an...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
ANNUAL REVIEW OF SOCIOLOGY, VOL 37
Volume:
37
Issue:
1
Pages:
131-153
Publication date:
2011-01-01
DOI:
EISSN:
1545-2115
ISSN:
0360-0572
Source identifiers:
170298
Language:
English
Keywords:
Pubs id:
pubs:170298
UUID:
uuid:1b71b60e-36eb-4bd7-98e7-4beb2220d577
Local pid:
pubs:170298
Deposit date:
2012-12-19

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