%0 Journal Article %1 Martijn2022 %A Martijn, Millecamp %A Conati, Cristina %A Verbert, Katrien %D 2022 %J User Modeling and User-Adapted Interaction %K explanation recommender %N 1 %P 215--252 %R 10.1007/s11257-021-09304-9 %T ``Knowing me, knowing you'': personalized explanations for a music recommender system %U https://doi.org/10.1007/s11257-021-09304-9 %V 32 %X Due to the prominent role of recommender systems in our daily lives, it is increasingly important to inform users why certain items are recommended and personalize these explanations to the user. In this study, we explored how explanations in a music recommender system should be designed to fit the preference of different personal characteristics. More specifically, we investigated three personal characteristics that influence the perception of explanations in music recommender system interfaces: need for cognition, musical sophistication, and openness. For each of these personal characteristics, we designed explanations for users with lower and higher levels of the personal characteristic. Afterward, we conducted for each personal characteristic a within-subject user study in which we compared the two explanations. Based on the results of these user studies, we provide design suggestions to adapt explanations to different levels of these three personal characteristics. In general, we suggest providing explanations up-front for all recommendations at once. For users low in need for cognition, displaying these explanations must be optional. To support users with low musical sophistication, we suggest providing brief explanations that do not require domain knowledge. For users with low openness, we suggest providing explanations with a lower number of explanation elements.

@article{Martijn2022, abstract = {Due to the prominent role of recommender systems in our daily lives, it is increasingly important to inform users why certain items are recommended and personalize these explanations to the user. In this study, we explored how explanations in a music recommender system should be designed to fit the preference of different personal characteristics. More specifically, we investigated three personal characteristics that influence the perception of explanations in music recommender system interfaces: need for cognition, musical sophistication, and openness. For each of these personal characteristics, we designed explanations for users with lower and higher levels of the personal characteristic. Afterward, we conducted for each personal characteristic a within-subject user study in which we compared the two explanations. Based on the results of these user studies, we provide design suggestions to adapt explanations to different levels of these three personal characteristics. In general, we suggest providing explanations up-front for all recommendations at once. For users low in need for cognition, displaying these explanations must be optional. To support users with low musical sophistication, we suggest providing brief explanations that do not require domain knowledge. For users with low openness, we suggest providing explanations with a lower number of explanation elements.}, added-at = {2022-11-06T03:23:15.000+0100}, author = {Martijn, Millecamp and Conati, Cristina and Verbert, Katrien}, biburl = {https://www.bibsonomy.org/bibtex/29d1d42f604cdba072b5f8f53dd0fa4b9/brusilovsky}, day = 01, doi = {10.1007/s11257-021-09304-9}, interhash = {a8a9024611a21d2748e5106acad98a8e}, intrahash = {9d1d42f604cdba072b5f8f53dd0fa4b9}, issn = {1573-1391}, journal = {User Modeling and User-Adapted Interaction}, keywords = {explanation recommender}, month = apr, number = 1, pages = {215--252}, timestamp = {2023-06-05T00:21:38.000+0200}, title = {``Knowing me, knowing you'': personalized explanations for a music recommender system}, url = {https://doi.org/10.1007/s11257-021-09304-9}, volume = 32, year = 2022 }