Authors: Dietmar Jannach, Alan Said, Marko Tkalčič, Markus Zanker
Abstract: In the area of recommender systems, the vast majority of research efforts is
spent on developing increasingly sophisticated recommendation models, also
using increasingly more computational resources. Unfortunately, most of these
research efforts target a very small set of application domains, mostly
e-commerce and media recommendation. Furthermore, many of these models are
never evaluated with users, let alone put into practice. The scientific,
economic and societal value of much of these efforts by scholars therefore
remains largely unclear. To achieve a stronger positive impact resulting from
these efforts, we posit that we as a research community should more often
address use cases where recommender systems contribute to societal good
(RS4Good). In this opinion piece, we first discuss a number of examples where
the use of recommender systems for problems of societal concern has been
successfully explored in the literature. We then proceed by outlining a
paradigmatic shift that is needed to conduct successful RS4Good research, where
the key ingredients are interdisciplinary collaborations and longitudinal
evaluation approaches with humans in the loop.
Source: http://arxiv.org/abs/2411.16645v1
