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.
%0 Generic
%1 citeulike:341231
%A Tyler, Joshua R.
%A Wilkinson, Dennis M.
%A Huberman, Bernardo A.
%D 2003
%K community email structure
%T Email as Spectroscopy: Automated Discovery of Community Structure within Organizations
%U http://arxiv.org/abs/cond-mat/0303264
%X 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.
@misc{citeulike:341231,
abstract = {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.},
added-at = {2007-08-15T12:01:56.000+0200},
author = {Tyler, Joshua R. and Wilkinson, Dennis M. and Huberman, Bernardo A.},
biburl = {https://www.bibsonomy.org/bibtex/26349c1459e01fa183c1423c36c33b191/wnpxrz},
citeulike-article-id = {341231},
eprint = {cond-mat/0303264},
interhash = {c712e59ff99f12c42a5d3c3b0bf4c48f},
intrahash = {6349c1459e01fa183c1423c36c33b191},
keywords = {community email structure},
month = Mar,
priority = {4},
timestamp = {2007-08-15T12:01:56.000+0200},
title = {Email as Spectroscopy: Automated Discovery of Community Structure within Organizations},
url = {http://arxiv.org/abs/cond-mat/0303264},
year = 2003
}