Considering emotions and contextual factors in music recommendation
Abstract
The main purpose of this paper is to present the results of a Systematic Literature Review (RSL) study that investigates music recommendation approaches that consider emotions and/or context (research question 1) as the main gaps and challenges that still remain and need to be addressed by future research (research question 2). After an extensive research, 64 publications were identified to answer the research questions. The studies were analyzed and evaluated for relevance. The main approaches that consider emotions and context were identified. The results of the review indicate that most studies in the field that combine multiple approach related to emotions or context factors have improved the user's hearing experience. The main contributions of the review are a set of aspects that we consider important to be addressed by the music recommendation systems. In addition, we also present a broad discussion about the challenges, difficulties and limitations that exist in music recommendation systems that consider emotions and contextual factors.
Keywords:
Music recommendation, Emotion, Context, User experience.
References
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Claire Carter. 2020. How Streaming Services Changed the Way We Listen to and Pay for Music. Ph.D. Dissertation. University of Mississippi.
Tuomas Eerola and Jonna K Vuoskoski. 2013. A review of music and emotion studies: approaches, emotion models, and stimuli. Music Perception: An Interdisciplinary Journal 30, 3 (2013), 307–340.
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Barbara Kitchenham, O Pearl Brereton, David Budgen, Mark Turner, John Bailey, and Stephen Linkman. 2009. Systematic literature reviews in software engineering–a systematic literature review. Information and software technology 51, 1 (2009), 7–15.
Peter Knees and Markus Schedl. 2013. A survey of music similarity and recommendation from music context data. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 10, 1 (2013), 1–21.
Litt D Vernon Lee. 2018. Music and Its Lovers: An Empirical Study of Emotional and Imaginative Responses to Music. Routledge.
Allan F Moore. 2013. Song means: Analysing and interpreting recorded popular song. Ashgate Publishing, Ltd.
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Yading Song. 2016. The Role of Emotion and Context in Musical Preference. Ph.D. Dissertation. Queen Mary University of London.
Chen-Ya Wang, Yu-Chi Wang, and Seng-Cho T Chou. 2018. A context and emotion aware system for personalized music recommendation. Journal of Internet Technology 19, 3 (2018), 765–779.
Claire Carter. 2020. How Streaming Services Changed the Way We Listen to and Pay for Music. Ph.D. Dissertation. University of Mississippi.
Tuomas Eerola and Jonna K Vuoskoski. 2013. A review of music and emotion studies: approaches, emotion models, and stimuli. Music Perception: An Interdisciplinary Journal 30, 3 (2013), 307–340.
Donald A Hodges. 2019. Music in the human experience: An introduction to music psychology. Routledge.
Joris H. Janssen, Van D. Broek, Egon L., and Joyce H.D.M. Westerink. 2012. Tune in to your emotions: A robust personalized affective music player. User Modeling and User-Adapted Interaction 22, 3 (2012), 255–279. https://doi.org/10.1007/s11257-011-9107-7
Barbara Kitchenham, O Pearl Brereton, David Budgen, Mark Turner, John Bailey, and Stephen Linkman. 2009. Systematic literature reviews in software engineering–a systematic literature review. Information and software technology 51, 1 (2009), 7–15.
Peter Knees and Markus Schedl. 2013. A survey of music similarity and recommendation from music context data. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 10, 1 (2013), 1–21.
Litt D Vernon Lee. 2018. Music and Its Lovers: An Empirical Study of Emotional and Imaginative Responses to Music. Routledge.
Allan F Moore. 2013. Song means: Analysing and interpreting recorded popular song. Ashgate Publishing, Ltd.
Bogdan Mróz. 2016. Online piracy: an emergent segment of the shadow economy. Empirical insight from Poland. Journal of Financial Crime (2016).
Yading Song. 2016. The Role of Emotion and Context in Musical Preference. Ph.D. Dissertation. Queen Mary University of London.
Chen-Ya Wang, Yu-Chi Wang, and Seng-Cho T Chou. 2018. A context and emotion aware system for personalized music recommendation. Journal of Internet Technology 19, 3 (2018), 765–779.
Published
2022-10-17
How to Cite
ASSUNÇÃO, Willian Garcias de; PICCOLO, Lara Schibelsky Godoy; ZAINA, Luciana Aparecida Martinez.
Considering emotions and contextual factors in music recommendation. In: INTERNATIONAL PAPERS - BRAZILIAN SYMPOSIUM ON HUMAN FACTORS IN COMPUTATIONAL SYSTEMS (IHC), 21. , 2022, Diamantina.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 247-249.
DOI: https://doi.org/10.5753/ihc_estendido.2022.225557.
