Bifrost inbox organizer: giving users control over the inbox
Proceedings of the second Nordic conference on Human-computer interaction
A language/action perspective on the design of cooperative work
CSCW '86 Proceedings of the 1986 ACM conference on Computer-supported cooperative work
Understanding email use: predicting action on a message
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Managers' email: beyond tasks and to-dos
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Beyond "from" and "received": exploring the dynamics of email triage
CHI '05 Extended Abstracts on Human Factors in Computing Systems
On the collective classification of email "speech acts"
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Detecting action-items in e-mail
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Using Speech Acts to Categorize Email and Identify Email Genres
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Email overload at work: an analysis of factors associated with email strain
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Improving Email Conversation Efficiency through Semantically Enhanced Email
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
Improving "email speech acts" analysis via n-gram selection
ACTS '09 Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech
Detecting emails containing requests for action
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A learning approach for email conversation thread reconstruction
Journal of Information Science
| Hi-index | 0.00 |
This paper presents a two-phased research project aiming to improve email triage for public administration managers. The first phase developed a typology of email classification patterns through a qualitative study involving 34 participants. Inspired by the fields of pragmatics and speech act theory, this typology comprising four top level categories and 13 subcategories represents the typical email triage behaviors of managers in an organizational context. The second study phase was conducted on a corpus of 1,703 messages using email samples of two managers. Using the k-NN (k-nearest neighbor) algorithm, statistical treatments automatically classified the email according to lexical and nonlexical features representative of managers' triage patterns. The automatic classification of email according to the lexicon of the messages was found to be substantially more efficient when k = 2 and n = 2,000. For four categories, the average recall rate was 94.32%, the average precision rate was 94.50%, and the accuracy rate was 94.54%. For 13 categories, the average recall rate was 91.09%, the average precision rate was 84.18%, and the accuracy rate was 88.70%. It appears that a message's nonlexical features are also deeply influenced by email pragmatics. Features related to the recipient and the sender were the most relevant for characterizing email. © 2012 Wiley Periodicals, Inc.