dweidai / text-arousal-and-valence-classification Goto Github PK

Two binary classifications regarding the input text data. The first classification is detecting the text’s valence level. Valence can be interpreted as the subject’s pleasant or unpleasant experience regarding the aspect or the topic of the text. If the text is positive in valence, that means the user who inputs the text is having a positive or pleasant attitude towards the subject matter; on the other hand, if the text is negative in valence, this means that the user is displeased or annoyed by the material. The other classification is regarding the arousal level. Arousal means the intensity of the stimulus to the subject. Positive arousal means that the subject matter might boost more adrenaline or higher blood pressure; negative arousal can be interpreted as tired, calm or other similar emotions. In all, using these two classifications, we can do a multi-class classification. We improved from the traditional binary emotion classification to the better quaternary emotion classification.