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Hi,

My method called SCAN and extension DISSECT can be used for identifying
communities using cohesive subgroups, centrality and similarity.

Chin A, Chignell M (2008) Automatic detection of cohesive subgroups within
social hypertext: A heuristic approach. New Review of Hypermedia and
Multimedia 14(1):121143

Chin, A., Chignell, M. DISSECT: Data-Intensive Socially Similar Evolving
Community Tracker. In Computational Social Network Analysis: Trends, Tools,
and Research Advances (Ed. Ajith Abraham, Aboul-Ella Hassanien, and Vaclav
Snasel), London: Springer-Verlag London Limited, 2010, 81-106.

Hope that helps.

Alvin

---------
Alvin Chin
Senior Researcher
Mobile Social Networking Group
Nokia Research Center, Beijing
http://research.nokia.com/people/alvin_chin


On Wed, Jan 6, 2010 at 4:13 PM, Peter J. Mucha <[log in to unmask]> wrote:

> *****  To join INSNA, visit http://www.insna.org  *****
>
> 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 <http://www.unc.edu/%7Emucha>
>
>
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