Creator: Strapparava, Carlo & Mihalcea, Rada
Description: This book chapter discusses annotating and identifying emotions in text. Abstract: This paper focuses on the classification of emotions and polarity in news headlines and it is meant as an exploration of the connection between emotions and lexical semantics. The authors first describe the construction of the data set used in evaluation exercise "Affective Text" task at SemEval 2007, annotated for six basic emotions: Anger, Disgust, Fear, Joy, Sadness, and Surprise, and for Positive and Negative polarity. The authors also briefly describe the participating systems and their results. Second, exploiting the same data set, the authors propose and evaluate several knowledge-based and corpus-based methods for the automatic identification of emotions in text.
Contributing Partner: UNT College of Engineering