Email as Spectroscopy: Automated Discovery of Community Structure within Organizations

dc.contributor.authorTyler, J.R.
dc.contributor.authorWilkinson, D.M.
dc.contributor.authorHuberman, B.A.
dc.date.accessioned2017-04-15T12:07:48Z
dc.date.available2017-04-15T12:07:48Z
dc.date.issued2003
dc.description.abstractWe 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.
dc.identifier.doi10.1007/978-94-017-0115-0_5
dc.identifier.isbn978-94-017-0115-0
dc.language.isoen
dc.publisherSpringer London, Dordrecht Amsterdam
dc.relation.ispartofCommunities and Technologies: Proceedings of the First International Conference on Communities and Technologies 2003
dc.relation.ispartofseriesCommunities and Technologies
dc.titleEmail as Spectroscopy: Automated Discovery of Community Structure within Organizations
dc.typeText
gi.citation.endPage96
gi.citation.startPage81
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