| Investigating gender fairness of recommendation algorithms in the music domain AB Melchiorre, N Rekabsaz, E Parada-Cabaleiro, S Brandl, O Lesota, ... Information Processing & Management 58 (5), 102666, 2021 | 107 | 2021 |
| Analyzing item popularity bias of music recommender systems: are different genders equally affected? O Lesota, A Melchiorre, N Rekabsaz, S Brandl, D Kowald, E Lex, ... Proceedings of the 15th ACM Conference on Recommender Systems, 601-606, 2021 | 52 | 2021 |
| LFM-2b: A dataset of enriched music listening events for recommender systems research and fairness analysis M Schedl, S Brandl, O Lesota, E Parada-Cabaleiro, D Penz, N Rekabsaz Proceedings of the 2022 Conference on Human Information Interaction and …, 2022 | 34 | 2022 |
| Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization. O Lesota, S Brandl, M Wenzel, AB Melchiorre, E Lex, N Rekabsaz, ... MORS@ RecSys, 2022 | 5 | 2022 |
| Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms. O Lesota, E Parada-Cabaleiro, S Brandl, E Lex, N Rekabsaz, M Schedl ISMIR, 291-297, 2022 | 2 | 2022 |
| Song lyrics have become simpler and more repetitive over the last five decades E Parada-Cabaleiro, M Mayerl, S Brandl, M Skowron, M Schedl, E Lex, ... Scientific Reports 14 (1), 5531, 2024 | | 2024 |
| Verse versus Chorus: Structure-aware Feature Extraction for Lyrics-based Genre Recognition. M Mayerl, S Brandl, G Specht, M Schedl, E Zangerle ISMIR, 884-890, 2022 | | 2022 |
| INTERACTIVELY EXPLORING SIMILARITIES BETWEEN MUSIC GENRES BASED ON USER-GENERATED TAGS S Brandl, M Schedl | | |
