E-Mail as Spectroscopy: Automated Discovery of Community Structure within Organizations

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Abstract
We describe a method for the automatic identification of communities of practice from e-mail logs within an organization. We use a betweenness centrality algorithm that can rapidly find communities within a graph representing information flows. We apply this algorithm to an initial e-mail corpus of nearly 1 million messages collected over a 2-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.

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