Tell Me What You Like and I Tell You What You Aim For: A Well-Being Centered Group Recommender System Using A Hybrid Approach

Julian Marvin Joers () and Ernesto William De Luca ()
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Julian Marvin Joers: Otto-Von-Guericke University
Ernesto William De Luca: Otto-Von-Guericke University

A chapter in People, Society, and Ethical Challenges of Information Systems, 2026, pp 219-228 from Springer

Abstract: Abstract In human-computer interaction (HCI) research, ensuring human well-being is seen as a key challenge. The consideration of well-being orientations, e.g. hedonia (aiming for pleasure, comfort, and relaxation) and eudaimonia (striving for authenticity, meaningfulness, excellence, and growth) is still at an early stage with regard to identification, measurement, and differentiability concerning expectations of technology. Particularly in the architectural design of recommender systems (RS), work is yet in the fledgling stage on how well-being can be considered in the development of RS. In this research in progress, we aim to present initial findings based on our labeled dataset (using the HEMA-Revised (HEMA-R) Scale (hedonia and eudaimonia)) of 2,946 items (movies, songs, and books) with the help of 229 participants. With a first architectural design on how the idea of well-being-centered RS can be implemented, we expand the research on group RS by introducing well-being-centered group RS.

Keywords: Recommender systems; Classification problem; Hedonic motives; Eudaimonic motives; Well-being in HCI; Well-being-centered recommender system (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-08486-6_15

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