University of Brighton Repository (University of Brighton) · 2006 · 16 citations · 0 references
ComputingComputer SciencePsychologyMachine LearningNatural Language ProcessingText AnalyticsAffective ComputingAffective State DetectionEmotion RecognitionMoodSentiment AnalysisSupport Vector MachinesAffective State RecognitionEmotion DetectionMood TypologySentiment ClassificationSupport Vector Machine ClassificationText-based Emotion AnalysisText-based Emotion DetectionText-based Emotion Recognition
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.