Personality and Emotions in Decision Making and Recommender Systems

Abstract. In this paper we survey the work on the usage of personality and emotions in recommender systems. Recommender systems are de-signed to support humans making better decisions. It has been shown that personality and emotions account for the variance in human de-cision making. We present various models and acquisition methods for emotions and personality. Furthermore, we showcase examples of effec-tive exploitation of personality and emotions in RS. We present in more details an example of the usage of emotions as implicit feedback for serendipitous recommendations