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Clustering of dyad distributions as a tool in network modeling

Frank, Ove; Hallinan, Maureen and Nowicki, Krzysztof LU (1985) In The Journal of Mathematical Sociology 11(1). p.47-64
Abstract
A general approach to exploratory analysis and modeling of network data is to investigate dyad distributions. We discuss clustering of dyad distributions when there are several variables defined on the vertices, and these variables interact with the arc values of the network. As an illustration we use data on achievement, race, sex and friendship for children in 48 different school classes. A clustering of the dyad distributions leads to the formulation of a log-linear model for friendship structure explained by achievement, race, and sex parameters. In particular, the example illustrates a way to find and display interaction structures in network data. We comment on how this approach is related to standard use of log-linear network models.
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
dyad distributions, cluster analysis, Network data, log-linear models
in
The Journal of Mathematical Sociology
volume
11
issue
1
pages
47 - 64
publisher
Routledge
external identifiers
  • scopus:84934652878
ISSN
1545-5874
DOI
10.1080/0022250X.1985.9989981
language
English
LU publication?
yes
id
01328a2d-5e90-4344-ad04-6543ad7a3d2a (old id 1782034)
date added to LUP
2011-02-03 17:21:34
date last changed
2017-07-30 04:40:05
@article{01328a2d-5e90-4344-ad04-6543ad7a3d2a,
  abstract     = {A general approach to exploratory analysis and modeling of network data is to investigate dyad distributions. We discuss clustering of dyad distributions when there are several variables defined on the vertices, and these variables interact with the arc values of the network. As an illustration we use data on achievement, race, sex and friendship for children in 48 different school classes. A clustering of the dyad distributions leads to the formulation of a log-linear model for friendship structure explained by achievement, race, and sex parameters. In particular, the example illustrates a way to find and display interaction structures in network data. We comment on how this approach is related to standard use of log-linear network models.},
  author       = {Frank, Ove and Hallinan, Maureen and Nowicki, Krzysztof},
  issn         = {1545-5874},
  keyword      = {dyad distributions,cluster analysis,Network data,log-linear models},
  language     = {eng},
  number       = {1},
  pages        = {47--64},
  publisher    = {Routledge},
  series       = {The Journal of Mathematical Sociology},
  title        = {Clustering of dyad distributions as a tool in network modeling},
  url          = {http://dx.doi.org/10.1080/0022250X.1985.9989981},
  volume       = {11},
  year         = {1985},
}