%0 Conference Paper %1 Htun_2021 %A Htun, Nyi Nyi %A Lecluse, Elisa %A Verbert, Katrien %B 26th International Conference on Intelligent User Interfaces %D 2021 %I ACM %K fairness group-recommendation iui2021 recommender %P 302-306 %R 10.1145/3397481.3450642 %T Perception of Fairness in Group Music Recommender Systems %U https://doi.org/10.1145%2F3397481.3450642 %X Fairness is an important aspect in group recommender systems (GRSs). They must ensure that potentially diverse preferences of all group members are taken into consideration when providing recommendations. Previous work has proposed a number of conflict elicitation and merging techniques to produce preferable recommendations for group members. However, we have yet to understand the influence of user personality on the perception of fairness in GRSs. To examine this gap, we use music recommendation as an example domain. We have developed a web-based group music recommender system using the Spotify API and two simple ranking algorithms: one based on the time the songs were voted by users (time-based) and the other based on a dissimilarity score (dissimilarity-based). A within-subjects experiment was conducted with 45 participants divided into groups of 3 (15 groups). Results showed that openness personality has a negative correlation with the perception that fairness is important in groups.

@inproceedings{Htun_2021, abstract = {Fairness is an important aspect in group recommender systems (GRSs). They must ensure that potentially diverse preferences of all group members are taken into consideration when providing recommendations. Previous work has proposed a number of conflict elicitation and merging techniques to produce preferable recommendations for group members. However, we have yet to understand the influence of user personality on the perception of fairness in GRSs. To examine this gap, we use music recommendation as an example domain. We have developed a web-based group music recommender system using the Spotify API and two simple ranking algorithms: one based on the time the songs were voted by users (time-based) and the other based on a dissimilarity score (dissimilarity-based). A within-subjects experiment was conducted with 45 participants divided into groups of 3 (15 groups). Results showed that openness personality has a negative correlation with the perception that fairness is important in groups.}, added-at = {2022-01-16T20:59:07.000+0100}, author = {Htun, Nyi Nyi and Lecluse, Elisa and Verbert, Katrien}, biburl = {https://www.bibsonomy.org/bibtex/2cf56ac1cf3d1b2a7adf4127c7207e5c2/brusilovsky}, booktitle = {26th International Conference on Intelligent User Interfaces}, description = {Perception of Fairness in Group Music Recommender Systems | 26th International Conference on Intelligent User Interfaces}, doi = {10.1145/3397481.3450642}, interhash = {c9ffd04bb2b93c23f5247212ab525d09}, intrahash = {cf56ac1cf3d1b2a7adf4127c7207e5c2}, keywords = {fairness group-recommendation iui2021 recommender}, month = apr, pages = {302-306}, publisher = {{ACM}}, timestamp = {2022-01-16T20:59:07.000+0100}, title = {Perception of Fairness in Group Music Recommender Systems}, url = {https://doi.org/10.1145%2F3397481.3450642}, year = 2021 }