Back to Search
Start Over
10. Settings in Social Networks: A Measurement Model
- Source :
- Sociological Methodology. 33:307-341
- Publication Year :
- 2003
- Publisher :
- SAGE Publications, 2003.
-
Abstract
- A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive structures, expressed by ultrametrics, and (2) the expected tie strength decreases with ultrametric distance. The approach could be described as model-based clustering with an ultrametric space as the underlying metric to capture the dependence in the observations. Bayesian methods as well as maximum-likelihood methods are applied for statistical inference. Both approaches are implemented using Markov chain Monte Carlo methods.
- Subjects :
- Theoretical computer science
Sociology and Political Science
Markov chain
business.industry
05 social sciences
050401 social sciences methods
Statistical model
Markov chain Monte Carlo
Bayesian inference
Machine learning
computer.software_genre
01 natural sciences
010104 statistics & probability
symbols.namesake
0504 sociology
Metric (mathematics)
symbols
Statistical inference
Artificial intelligence
0101 mathematics
Cluster analysis
business
Ultrametric space
computer
Mathematics
Subjects
Details
- ISSN :
- 14679531 and 00811750
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- Sociological Methodology
- Accession number :
- edsair.doi...........7dffe091344ecf9fdc2aa7f1a3c3372c