Online social networking tools may facilitate knowledge exchange
by allowing users to share information and develop relationships
with others near them in their social network. However
maintaining complete, up-to-date social network information is
challenging, requiring users to provide continuous, explicit access
to their personal relationship data. We explore the viability of
using public mailing lists in a corporate environment to
automatically approximate social relationships. We found that co-
memberships in mailing lists provided a reasonably accurate
indication of who works with whom. We then explored whether
people would find such social networking information valuable in
seeking out or providing information to others. We found that
organizational distance, social status, and informal social
connections had a meaningful impact on whom users would chose
to meet for sharing knowledge.
%0 Unpublished Work
%1 farnham2003
%A Farnham, Shelly
%A Portnoy, Will
%A Turski, Andrzej
%D 2003
%K behavioral_data data_mining mailing_lists social_networks stasi2.0
%T Approximating Social Networks from Public Mailing Lists
%U http://www.farnhamresearch.com/papers/approximatingsocialnetworks.pdf
%X Online social networking tools may facilitate knowledge exchange
by allowing users to share information and develop relationships
with others near them in their social network. However
maintaining complete, up-to-date social network information is
challenging, requiring users to provide continuous, explicit access
to their personal relationship data. We explore the viability of
using public mailing lists in a corporate environment to
automatically approximate social relationships. We found that co-
memberships in mailing lists provided a reasonably accurate
indication of who works with whom. We then explored whether
people would find such social networking information valuable in
seeking out or providing information to others. We found that
organizational distance, social status, and informal social
connections had a meaningful impact on whom users would chose
to meet for sharing knowledge.
@unpublished{farnham2003,
abstract = {Online social networking tools may facilitate knowledge exchange
by allowing users to share information and develop relationships
with others near them in their social network. However
maintaining complete, up-to-date social network information is
challenging, requiring users to provide continuous, explicit access
to their personal relationship data. We explore the viability of
using public mailing lists in a corporate environment to
automatically approximate social relationships. We found that co-
memberships in mailing lists provided a reasonably accurate
indication of who works with whom. We then explored whether
people would find such social networking information valuable in
seeking out or providing information to others. We found that
organizational distance, social status, and informal social
connections had a meaningful impact on whom users would chose
to meet for sharing knowledge.
},
added-at = {2008-08-09T13:23:40.000+0200},
author = {Farnham, Shelly and Portnoy, Will and Turski, Andrzej},
biburl = {https://www.bibsonomy.org/bibtex/275111638b6207458bc18732ec261ca66/edna_foobar},
interhash = {7a008d8b8ff2b8f767fab87ef07f6b58},
intrahash = {75111638b6207458bc18732ec261ca66},
keywords = {behavioral_data data_mining mailing_lists social_networks stasi2.0},
timestamp = {2008-08-09T13:23:41.000+0200},
title = {Approximating Social Networks from Public Mailing Lists},
url = {http://www.farnhamresearch.com/papers/approximatingsocialnetworks.pdf},
year = 2003
}