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Thanks to Jim for mentioning our methodology for identifying communities
across multiple times (and/or multiple scales, types of connections).
The reference is
Mucha, Peter J, Thomas Richardson, Kevin Macon, Mason A. Porter, and
Jukka-Pekka Onnela. 2009. Community Structure in Time-Dependent,
Multiscale, and Multiplex Networks. submitted.
http://arxiv.org/abs/0911.1824.
This is of course not the only way to study communities in dynamic
data---see the reviews previously mentioned in this thread---but it has
the property of being intimately related to the existing modularity
methodologies for community detection, which is IMHO nice for many
circumstances.
Peter
--
Peter J. Mucha, Associate Professor
Department of Mathematics
Carolina Center for Interdisciplinary Applied Mathematics
Institute for Advanced Materials, Nanoscience and Technology
The University of North Carolina at Chapel Hill
Campus Box #3250, UNC, Chapel Hill, NC 27599-3250
Phone: 919/843-2550, Fax: 919/962-9345, Office: 304B Phillips Hall
[log in to unmask], http://www.unc.edu/~mucha
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