Name
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 bi- nary classifiers, and show that a typology of affective states proposed by Scherer's et al is a good starting point for more refined analysis. |
Year | Venue | Field |
|---|---|---|
2006 | AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs | Mood,Computer science,Support vector machine,Typology,Artificial intelligence,Affect (psychology),Machine learning,Binary number |
DocType | Citations | PageRank |
Conference | 3 | 0.44 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michel Généreux | 1 | 3 | 0.44 |
| Roger Evans | 2 | 344 | 55.12 |