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Considering emotions and contextual factors in music recommendation: a systematic literature review

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Abstract

In recent years, several music recommendation systems have been developed with the aim of incorporating valuable information into the user’s modeling and recommendation process. The inclusion of emotions and contextual information in music recommendation applications is increasingly becoming a relevant aspect to improve the listening experience. Thus, the main aim of this systematic literature review (SLR) is investigating the music recommendation approaches that considers emotions and/or context (research question 1) as well as to identify 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 this review are a set of aspects that we consider important to be addressed by the music recommendation systems, such as: user activity, satisfaction, feedback, cold-start problems, cognitive load, learning, personality, and user preference. 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.

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Notes

  1. https://www.spotify.com/

  2. https://soundcloud.com/

  3. https://www.last.fm/

  4. https://www.apple.com/apple-music/

  5. https://www.spotify.com/

  6. https://www.last.fm

  7. https://www.apple.com/apple-music/

  8. https://www.deezer.com/en/

  9. https://www.statista.com/statistics/669113/number-music-streaming-subscribers/

  10. https://scholar.google.com

  11. http://www.writewords.org.uk/

  12. https://dl.acm.org/

  13. https://ieeexplore.ieee.org/

  14. https://www.scopus.com/

  15. https://www.sciencedirect.com/

  16. https://link.springer.com/

  17. https://parsif.al/

  18. Appendix—https://appendix.herokuapp.com/

  19. https://parsif.al/

  20. https://www.livejournal.com/

  21. https://www.spotify.com/

  22. https://www.deezer.com/

  23. https://www.apple.com/apple-music/

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Authors and Affiliations

  1. Department of Computer Science, Federal University of Sao Carlos, Sao Carlos, Brazil

    Willian G. Assuncao & Luciana A. M. Zaina

  2. Knowledge Media Institute, The Open University, Milton Keynes, UK

    Lara S. G. Piccolo

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  1. Willian G. Assuncao
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  2. Lara S. G. Piccolo
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  3. Luciana A. M. Zaina
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Correspondence to Willian G. Assuncao.

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Assuncao, W.G., Piccolo, L.S.G. & Zaina, L.A.M. Considering emotions and contextual factors in music recommendation: a systematic literature review. Multimed Tools Appl 81, 8367–8407 (2022). https://doi.org/10.1007/s11042-022-12110-z

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