Abstract
We describe a method for the automatic identification of communities of practice from email 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 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.
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Tyler, J.R., Wilkinson, D.M., Huberman, B.A. (2003). Email as Spectroscopy: Automated Discovery of Community Structure within Organizations. In: Huysman, M., Wenger, E., Wulf, V. (eds) Communities and Technologies. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0115-0_5
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DOI: https://doi.org/10.1007/978-94-017-0115-0_5
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