Distinguishing Affective States in Weblog Posts

Michel Genereux, Roger Evans

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.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.