Email as Spectroscopy: Automated Discovery of Community Structure within Organizations
| dc.creator | Tyler, Joshua R. | |
| dc.creator | Wilkinson, Dennis M. | |
| dc.creator | Huberman, Bernardo A. | |
| dc.date | 2003-03-14 | |
| dc.date | 2003-03-20 | |
| dc.date.accessioned | 2026-07-07T02:50:10Z | |
| dc.date.available | 2026-07-07T02:50:10Z | |
| dc.description | 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. | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0303264 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0303264 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/21017 | |
| dc.subject | Statistical Mechanics | |
| dc.title | Email as Spectroscopy: Automated Discovery of Community Structure within Organizations | |
| dc.type | text |