Evaluating user experience in music discovery on deezer and spotify


A music recommendation system aims to proactively suggest items of interest to users based on their behavior, purpose, or previous listening. Traditionally, recommendations are evaluated by the performance of the algorithms, especially in prediction accuracy. However, researchers have recently started investigating system effectiveness using evaluation criteria aimed at the users' perspective. Research in the field of Recommendation Systems (RS) has demonstrated that considering user experience (UX) concepts in the recommendation generation process can impact in terms of user values and that besides the accuracy of the algorithms, other factors influence the music listening experience. These factors can involve system aspects, personal aspects, or situational aspects. In this sense, this work aims to present the results of an exploratory study conducted with two commercial music platforms (Spotify and Deezer). The study analyzed the interaction between music listeners with the two platforms. In addition, we checked how the user experience was related to other aspects (e.g., satisfaction, user activity, feedback, and others) that influenced listening preferences. The study was conducted with 10 participants. We used the Communicability Evaluation Method (CEM) to detect communicability failures focusing on the user and the Self-Assessment Manikin (SAM) questionnaire. The results show that the recommendation methods of the two platforms do not sufficiently consider the desirable aspects. Furthermore, users expressed dissatisfaction with the first recommendations received by the platforms.
Palavras-chave: Affective computing, Emotion recognition, Music information retrieval, Music recommendation, User experience


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ASSUNÇÃO, Willian Garcias de; ZAINA, Luciana Aparecida Martinez. Evaluating user experience in music discovery on deezer and spotify. In: SIMPÓSIO BRASILEIRO SOBRE FATORES HUMANOS EM SISTEMAS COMPUTACIONAIS (IHC), 21. , 2022, Diamantina. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 .