Name
Abstract | ||
|---|---|---|
Email is a key communication tool for collaborative work- groups. In this paper, we investigate how team leadership roles can be inferred from a collection of email messages exchanged among team members. This task can be useful to monitor group leader's performance, as well as to study other aspects of work group dynamics. Using a large email collection with several workgroups whose leaders were pre- viously defined, we demonstrate that leadership positions can be predicted by a combination of trac-based and text- based email patterns. Trac-based patterns consist of in- formation patterns that can be extracted from the message headers, such as frequency counts, message thread position and whether the message was broadcast to the entire work- group or not. Textual patterns are represented by the mes- sage's "email speech acts",i.e., semantic information with the sender's intent that can be automatically inferred by language usage. Using o-the-shelf learning algorithms, we obtained 96% accuracy and 88.2% in F-measure in predict- ing the leadership roles on 34 email-centered work groups. |
Year | Venue | Keywords |
|---|---|---|
2007 | CEAS | working group |
DocType | Citations | PageRank |
Conference | 2 | 0.37 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vitor R. Carvalho | 1 | 672 | 36.38 |
| Wen Wu | 2 | 517 | 47.40 |
| William W. Cohen | 3 | 10178 | 1243.74 |