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Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects models
Open accessAbstract
Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does.
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Cites
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051
Exploratory Social Network Analysis with Pajek
de Nooy, W., Mrvar, A., & Batagelj, V. (2005) · doi:10.1017/cbo9780511806452 · Cited by 1,244
Social Structure from Multiple Networks. II. Role Structures
Boorman, S. A., & White, H. C. (1976) · American Journal of Sociology · doi:10.1086/226228 · Cited by 788
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A Survey of Statistical Network Models
Goldenberg, A., Zheng, A. X., Fienberg, S. E., & Airoldi, E. M. (2010) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000005 · Cited by 819
Dynamics and Control of Diseases in Networks with Community Structure
Salathé, M., & Jones, J. H. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000736 · Cited by 586
Exponential-family random graph models for valued networks
Krivitsky, P. N. (2012) · Electronic Journal of Statistics · doi:10.1214/12-ejs696 · Cited by 295
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Metadata
- Authors
- Krivitsky, P. N., Handcock, M. S., Raftery, A. E., & Hoff, P. D.
- Venue
- Social Networks
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 31
- Issue
- 3
- Pages
- 204-213
- ISSN
- 0378-8733 (ISSN-L)
- OpenAlex
- W2019144999
- Cited by
- 284
- References
- 3
- FWCI
- 5.10
- Type
- journal article
- Language
- en
- Open access
- green
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- Krivitsky, P. N., Handcock, M. S., Raftery, A. E., & Hoff, P. D. (2009). Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects models. Social Networks. https://doi.org/10.1016/j.socnet.2009.04.001
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