  We describe a methodology for the automatic identification of communities of
practice from email logs within an organization. We use a betweeness centrality
algorithm that can rapidly find communities within a graph representing
information flows. We apply this algorithm to an email corpus of nearly one
million messages collected over a two-month span, and show that the method is
effective at identifying true communities, both formal and informal, within
these scale-free graphs. This approach also enables the identification of
leadership roles within the communities. These studies are complemented by a
qualitative evaluation of the results in the field.
