  We present DEGARI (Dynamic Emotion Generator And ReclassIfier), an
explainable system for emotion attribution and recommendation. This system
relies on a recently introduced commonsense reasoning framework, the TCL logic,
which is based on a human-like procedure for the automatic generation of novel
concepts in a Description Logics knowledge base. Starting from an ontological
formalization of emotions based on the Plutchik model, known as ArsEmotica, the
system exploits the logic TCL to automatically generate novel commonsense
semantic representations of compound emotions (e.g. Love as derived from the
combination of Joy and Trust according to Plutchik). The generated emotions
correspond to prototypes, i.e. commonsense representations of given concepts,
and have been used to reclassify emotion-related contents in a variety of
artistic domains, ranging from art datasets to the editorial contents available
in RaiPlay, the online platform of RAI Radiotelevisione Italiana (the Italian
public broadcasting company). We show how the reported results (evaluated in
the light of the obtained reclassifications, the user ratings assigned to such
reclassifications, and their explainability) are encouraging, and pave the way
to many further research directions.
