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An Exploratory Study on the Spotify Recommender System

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Information Systems and Technologies (WorldCIST 2022)

Abstract

Spotify is a world class platform for music streaming, and it offers various kinds of services. As with many digital platforms, Spotify uses artificial intelligence to personalize the user experience, also known as a recommender system. This study investigates what role Spotify’s recommender system plays in the use of Spotify and if there are any differences in satisfaction between different ages and gender. Therefore, we conducted a survey about how customers are using Spotify, which was shared in different forums. In total we received 159 answers with respondents from 21 different countries. One of the main findings was that the three services “Make your own playlist”, “Playlist made by Spotify” and “Recommended songs” are the most popular. Also, a correlation was made to investigate the relationship between the satisfaction of “Recommended songs” and if customers add them to their own playlists. The Spearman’s Rank Correlation Coefficient was 0.43 (significant at the 0.01 level), which is a moderate value. This means that almost half of the time the Spotify users place the recommended songs in their playlist. Further, two conclusions were arrived at. Firstly, the recommender system plays a major part in how customers use Spotify. Secondly, we cannot see that age and gender would significantly affect the satisfaction of the recommended songs that Spotify suggest.

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Acknowledgements

The authors would like to thank the respondents to the anonymous survey for their time and availability.

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Correspondence to Manuel Au-Yong-Oliveira .

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Appendix A – Spearman’s Rank Correlation Coefficient Calculation

Appendix A – Spearman’s Rank Correlation Coefficient Calculation

Variable X: “How often are you satisfied with the songs that Spotify recommends?”

Variable Y: “How often do you add a recommended song to your playlist?”

figure a

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Björklund, G., Bohlin, M., Olander, E., Jansson, J., Walter, C.E., Au-Yong-Oliveira, M. (2022). An Exploratory Study on the Spotify Recommender System. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-031-04819-7_36

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