Figure 1

Recommendation accuracy measured by the mean absolute error (MAE) of a non-negative matrix factorization-based approach (i.e., NMF [10]) and a neighborhood-based approach (i.e., UserKNN [11]) for mainstream and beyond-mainstream user groups in Last.fm. We see that beyond-mainstream users receive a substantially lower recommendation quality (i.e., higher MAE) compared to mainstream music listeners. Thus, for recommender systems, it is harder to provide high-quality recommendations to beyond-mainstream than to mainstream listeners