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As I understand, the p1, p2, p* models are used to model network ties as 
independent variable, possibly using actor attributes as explanatory 

Could you please point me to work/method that addresses the reverse 
problem of modeling attribute data from the network structure? In this 
case the attributes are dependent variables and should be explained by 
the network ties plus attribute data of alters and other actors in the 
network. I am especially interested in predicting categorical data with 
large number of categories. My background is in computer science and I 
am looking at using social networks for collaborative filtering. I would 
be interested in how social network scientists have approached or would 
approach this problem.

I'll post a summary of the answers to the list - please let me know if 
you want me to keep your reply private.

Thank you for your advice,


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