A complementary account to emotion extraction and classification in cultural heritage based on the Plutchik’s theory

Abstract

The paper presents a combined approach to knowledge-based emotion attribution and classification of cultural items employed in the H2020 project SPICE. In particular, we show a preliminary experimentation conducted on a selection of items contributed by the GAM Museum in Turin (Galleria di Arte Moderna), pointing out how different language-based approaches to emotion categorization (used in the systems Sophia and DEGARI respectively) can be powerfully combined to cope with both coverage and extended affective attributions. Interestingly, both approaches are based on an ontology of the Plutchik's theory of emotions.

DEGARI 2.0: A diversity-seeking, explainable, and affective art recommender for social inclusion

“…Concerning the emojis included in the artwork annotation panel (love, curiosity, delight, joy, fear, sadness and disgust), the selection was driven by the museum curators based on their experience with the social media of the institution, and with the preferences of the audience of teenagers. On the other hand, following the considerations put forth in (Bolioli et al (2022) for emotion extraction in artwork annotation, the association between emojis and emotions was established based on Emojipedia (https://emojipedia.org/), which, in the last decade, has become an authoritative source for interpreting emojis' meaning (Rodrigues et al (2018).…”