Emotions influence everyday decisions. When people make decisions about movies to watch, songs to listen or even about more serious issues such as health, they perform a cognitive process that estimates which of various alternative choices would yield the most positive consequences. Indeed, this process in not totally rational because it is influenced, directly or in a subtle way by personality traits and emotions. In this paper we propose the idea of defining an affective user profile, which can act as a computational model of personality and emotions, included in a general, affective-aware, recommendation framework.
['Marco Polignano']
A framework for emotion-aware recommender systems supporting decision making