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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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