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.
%0 Journal Article
%1 Tyler:2003p592
%A Tyler, Joshua R
%A Wilkinson, Dennis M
%A Huberman, Bernardo A
%D 2003
%J Communities and Technologies: Proceedings of the First łdots
%K imported
%T Email as Spectroscopy: Automated Discovery of Community Structure within Organizations
%U http://books.google.com/books?hl=en&lr=&ie=UTF-8&id=u5v9f4KKHxsC&oi=fnd&pg=PA81&dq=Nt3RLUy1AXsJ:scholar.google.com/&ots=InU64p7A6A&sig=zXZ-zdemIYAvb_beYADPl-deOAo
%X 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.
@article{Tyler:2003p592,
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. },
added-at = {2008-03-13T16:33:57.000+0100},
author = {Tyler, Joshua R and Wilkinson, Dennis M and Huberman, Bernardo A},
biburl = {https://www.bibsonomy.org/bibtex/20e818ade6ffc29c71577277104f99372/bertil.hatt},
date-added = {2007-06-25 04:33:52 +0200},
date-modified = {2008-03-13 14:45:05 +0100},
description = {March 2008},
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intrahash = {0e818ade6ffc29c71577277104f99372},
journal = {Communities and Technologies: Proceedings of the First {\ldots}},
keywords = {imported},
local-url = {file://localhost/Users/bertilhatt/Documents/Papers/Tyler/2003/Tyler%202003%20Communities%20and%20Technologies%20Proceedings%20of%20the%20First%20%E2%80%A6.pdf},
month = Jan,
pmid = {8863564880432717110related:Nt3RLUy1AXsJ},
rating = {3},
read = {Yes},
timestamp = {2008-03-13T16:34:24.000+0100},
title = {Email as Spectroscopy: Automated Discovery of Community Structure within Organizations},
uri = {papers://C3B117CD-23C4-4854-9426-AC96AFB113DA/Paper/p592},
url = {http://books.google.com/books?hl=en&lr=&ie=UTF-8&id=u5v9f4KKHxsC&oi=fnd&pg=PA81&dq=Nt3RLUy1AXsJ:scholar.google.com/&ots=InU64p7A6A&sig=zXZ-zdemIYAvb_beYADPl-deOAo},
year = 2003
}