We introduce a new emotion classification task based on Leary's Rose, a framework for interpersonal communication. We present a small dataset of 740 Dutch sentences, outline the annotation process and evaluate an-notator agreement. We then evaluate the performance of several automatic classification systems when classifying individual sentences according to the four quadrants and the eight octants of Leary's Rose. SVM-based classifiers achieve average F-scores of up to 51 % for 4-way classification and 31% for 8-way classification, which is well above chance level. We conclude that emotion classification according to the Interpersonal Circumplex is a challenging task for both humans and machine learners. We expect classification performance to increase as context information becomes available in future versions of our dataset.
展开▼
