Distinguishing affective states in weblogs

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.