Identifying Community Structures from Network Data via Maximum Likelihood Methods
Networks of social and economic interactions are often influenced by unobserved structures among the nodes. Based on a simple model of how an unobserved community structure generates networks of interactions, we axiomatize a method of detecting the latent community structures from network data. The method is based on maximum likelihood estimation.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 9 (2009)
Issue (Month): 1 (September)
|Contact details of provider:|| Web page: http://www.degruyter.com|
|Order Information:||Web: http://www.degruyter.com/view/j/bejte|
When requesting a correction, please mention this item's handle: RePEc:bpj:bejtec:v:9:y:2009:i:1:n:30. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla)
If references are entirely missing, you can add them using this form.