Abstract
This short paper reports on initial experiments on the use of binary classifiers to distinguish affective states in weblog posts. Using a corpus of English weblog posts, annotated for mood by their authors, we trained support vector machine binary classifiers, and show that a typology of affective states proposed by Scherer’s et al is a good starting point for more refined analysis.
Original language | English |
---|---|
Title of host publication | Computational Approaches to Analyzing Weblogs, Papers from the 2006 AAAI Spring Symposium, Technical Report SS-06-03 |
Publisher | The AAAI Press |
Pages | 40-42 |
Number of pages | 3 |
ISBN (Print) | 9781577352648 |
Publication status | Published - Mar 2006 |
Event | Computational Approaches to Analyzing Weblogs, Papers from the 2006 AAAI Spring Symposium, Technical Report SS-06-03 - Stanford, California, USA Duration: 1 Mar 2006 → … |
Conference
Conference | Computational Approaches to Analyzing Weblogs, Papers from the 2006 AAAI Spring Symposium, Technical Report SS-06-03 |
---|---|
Period | 1/03/06 → … |
Bibliographical note
© 2006 American Association for Artificial IntelligenceKeywords
- Weblogs
- Language analysis