Prediction of Hedonic and Eudaimonic Characteristics from User Interactions
Marko Tkalčič, Elham Motamedi, Francesco Barile, Eva Puc, Urša Mars Bitenc · 2022
Content-based recommender (CBR) systems take advantage of item characteristics and user propensities for these characteristics in order to select the items that are better suited for a user. Related work has shown that the characteristics of hedonia (pleasure) and eudaimonia (deeper meaning) account for user preferences in the domain of movies. However, labeling items with hedonic/eudaimonic properties and measuring user propensity for eudaimonic/hedonic experiences could be done only through questionnaires. In this work we present the results of our work-in-progress on the prediction of user propensities for eudaimonic and hedonic experiences from a movie preferences dataset. Our results indicate that a range of classifiers that use ratings of movies as features perform substantially better than the average baseline.