A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification

The advent of computational tools and methods for investigating the way we respond to objects and situations has paved the way to a deeper understanding of the intricate relationship between emotions and artistic content. For example, [55] have studied how art affects emotional regulation by measuring the brain response through EEG: their research shows that, in comparison with photographs depicting real events, artworks determine stronger electro-physiological responses; in parallel, [19] argue that the emotional response to art - measured through facial muscle movements - is attenuated in art critics, and stronger in non-expert, thus showing the universality and spontaneity of this response. The association between art and emotions is even stronger when the artistic expression is conveyed by media, as in music and movies. For example, music has proven to be an effective tool for emotion regulation: as demonstrated by [54], music can induce specific emotional states in everyday situations, an effect which is sought for by the users and can be exploited to create effective affective recommender systems [3]. Finally, emotional engagement is of primary importance in narrative media, such as film and television, as extensively investigated by a line of research which draws from both film studies and emotion theories [47, 53]. As a consequence of the multifaceted, complex role played by emotions in the experience of art and media, the investigation of this phenomenon with computational tools has relied on a variety of models and methodologies, ranging from dimensional models, better suited to investigate physiological, continuous correlate of emotions [45, 57, 29], to categorical models, which lend themselves to inspecting the conscious level of emotional experience [39, 12, 4]. Dimensional models typically measure the emotional engagement along the arousal and hedonic axes, and are useful to study how the emotional response evolves over time.