Of funnels, filters and compasses: Economy, technique and subjectivity in Spotify

Authors

  • Lucas Bazzara

DOI:

https://doi.org/10.24215/23143924e028

Keywords:

Spotify, business model, ,algorithmic models, profile, personalization

Abstract

In this paper we will do an in-depth analysis of Spotify, as it is the maximum reference among music streaming platforms, a fact that can be seen in its massive use and market position. This will not preclude giving a sufficiently comprehensive definition that refers to music streaming platforms in general, but such a definition will function as a starting point from which the most emblematic economic and cultural case will be examined in detail. In this way, and based on the articulation that operates in Spotify between economics, technique and subjectivity, the questions that will guide the development of the work will be: What is its business model, or what market logic does it put into play? What is its subjective model, or what type of ideal user or listener does it configure? And what computing technologies does it use to "unite the interests of industries and users"? As you will see, terms such as freemium, machine learning, recommendation system, profile and personalization will be key to unraveling this platform logic.

Downloads

Download data is not yet available.

References

Arcila-Calderón, C., Sánchez-Holgado, P. y Ordóñez González K. (2019). Las plataformas de entretenimiento on-demand: detrás del Machine Learning de Netflix, HBO y Spotify. En Romero Rodríguez, L.M. y Rivera Rogel, D.E. (Coords.). La comunicación en el escenario digital. Actualidad, retos y prospectivas (pp. 645-669). Pearson. http://tec-comunicacion.unsl.edu.ar/Tecno%20I/2019/Teor%EDas/Documentos/La_comunicacion_en_el_escenario_digital.pdf

Arrese, A. (2004). Algunas consideraciones sobre la gestión de productos y contenidos de los medios. Comunicación y sociedad, XVII (2), 9-44.

Becerra, M., Labate, C., Lozano, L., Marino, S. y Mastrini, G. (2013). Abordajes sobre el concepto de ‘concentración’. En Mastrini, G., Bizberge, A. y de Charras, D. (Eds.). Las políticas de comunicación en el Siglo XXI. Nuevos y viejos desafíos (pp. 139-174). La Crujía.

Chevalier Naranjo, S. (2021). El steaming, una segunda vida para la industria musical. Statista. https://es.statista.com/grafico/9156/ingresos-del-mercado-mundial-de-la-musica-grabada/

Chodos, A.T. (2019). What does music mean to Spotify? An essay on musical significance in the era of digital curation. INSAM: Journal of Contemporary Music, Art and Technology, 1 (2), 36-64.

Deleuze, G. (1999). Posdata sobre las sociedades de control. En Ferrer, Christian (Comp). El lenguaje libertario. Antología del pensamiento anarquista contemporáneo (pp. 105-110). Altamira.

Eriksson, M. (2018). Unpacking Online Streams. APRJA, 7, (1). https://doi.org/10.7146/aprja.v7i1.115066

Eriksson, M., Fleischer, R., Johansson, A., Snickars, P. y Vonderau, P. (2019). Spotify Teardown. Inside the Black Box of Streaming Music. MIT Press.

García, J. (2020). Quién está ganando la guerra del streaming de música. Xataka. https://www.xataka.com/empresas-y-economia/quien-esta-ganando-guerra-streaming-musica

IFPI (2021). Global Music Report 2021. State of the Industry. https://www.ifpi.org/wp-content/uploads/2020/03/GMR2021_STATE_OF_THE_INDUSTRY.pdf

Kassabian, A. (2013). Introduction. Ubiquitous Listening: Affect, Attention and Distributed Subjectivity. University of California Press.

Lury, C. y Day, S. (2019). Algorithmic Personalization as a mode of individuation. Theory, Culture and Society, 0 (0), 1-21. https://doi.org/10.1177/0263276418818888

Monzoncillo, J. M. (2011). Las nuevas televisiones: personalización e individualización. La televisión etiquetada. Nuevas audiencias y nuevos negocios (pp. 83-101). Planeta.

Nylund Hagen, A. (2015). Using Music Streaming Services: Practices, Experiences and the Lifeworld of Musicking. [Tesis doctoral, Faculty of Humanities, University of Oslo]. https://www.academia.edu/21823524/Using_Music_Streaming_Services_Practices_Experiences_and_the_Lifeworld_of_Musicking

Ortelli, M. (2016). Radiohead. La banda del futuro. Página/12. https://www.pagina12.com.ar/diario/suplementos/radar/9-11510-2016-05-22.html

Pichl, M.; Zangerle, E. y Specht, G. (2015). Towards a context-aware music recommendation approach: what is hidden in the playlist name? IEEE 15th International Conference on Data Mining Workshop (pp. 1360-1365). DOI 10.1109/ICDMW.2015.145

Portugal, I., Alencar, P. y Cowan, D. (2018). The use of machine learning algorithms in recommender systems: A systematic review. arXiv, 4, 1-16. https://arxiv.org/ftp/arxiv/papers/1511/1511.05263.pdf

Prey, R. (2018). Nothing Personal. Algorithmic individuation on music streaming platforms. Media, Culture and Society, 40 (7), 1086-1100. Sage Publications. https://journals.sagepub.com/doi/full/10.1177/0163443717745147

Rodríguez, P. (2019). Las palabras en las cosas. Saber, poder y subjetivación entre algoritmos y biomoléculas. Cactus.

Rodríguez, P. (2018). Gubernamentalidad algorítmica. Sobre las formas de subjetivación en la sociedad de los metadatos. Revista Barda, 4, (6), 14-35. https://www.cefc.org.ar/assets/files/rodriguez.pdf

Rus, C. (2020). Spotify va a por todas con el podcast: compra Gimlet Media, una de las principales redes de podcast a nivel mundial. Xataka. https://www.xataka.com/servicios/spotify-va-a-todas-podcast-compra-gimlet-media-principales-redes-podcasts-a-nivel-mundial

Sanjinés Flores, D.E. (2019). Sistema para la Minería de Opiniones. Avances en Informática y Automática. Duodécimo Workshop (pp. 97-109). https://gredos.usal.es/handle/10366/139439

Spotify for Artists (2019). How ‘Fans Also Like’ Works. https://artists.spotify.com/blog/how-fans-also-like-works

Spotify Investors (2021). Press Release Details: Spotify Technology S.A. Announces Financial Results for First Quarter 2021. https://investors.spotify.com/financials/press-release-details/2021/Spotify-Technology-S.A.-Announces-Financial-Results-for-First-Quarter-2021/default.aspx

Spotify Labs (2020). For Your Ears Only: Personalizing Spotify Home With Machine Learning. https://labs.spotify.com/2020/01/16/for-your-ears-only-personalizing-spotify-home-with-machine-learning/

Spotify Technology S.A. (2018). Prospectus. Form F-1 Registration Statement. United States Securities and Exchange Comission. https://www.sec.gov/Archives/edgar/data/1639920/000119312518063434/d494294df1.htm

Srnicek, N. (2018). Capitalismo de plataformas. Caja Negra.

Sweney, M. (2018). Slipping discs: music streaming revenues of $6.6bn surpass CD sales. The Guardian. https://www.theguardian.com/technology/2018/apr/24/music-streaming-revenues-overtake-cds-to-hit-66bn

Terranova, T. (2017). “Red Stack Attack! Algoritmos, capital y la automatización del común”. Avanessian, A. y Reis, M. (Comps.). Aceleracionismo. Estrategias para una transición hacia el postcapitalismo. Caja Negra.

Vonderau, P. (2017). The Spotify Effect: Digital Distribution and Financial Growth. Television and New Media, 20, (1), 1-17. https://www.academia.edu/35208651/The_Spotify_Effect_Digital_Distribution_and_Financial_Growth

Wang, A. (2019). ‘Spotify Teardown’ Is The Book Spotify Didn’t Want Published. Rolling Stone. https://www.rollingstone.com/pro/features/spotify-teardown-book-streaming-music-790174/

Wikström, P. (2014). La industria musical en una era de distribución digital. C@MBIO. 19 ensayos fundamentales sobre cómo internet está cambiando nuestras vidas. BBVA Open Mind. https://www.bbvaopenmind.com/libros/cambio-19-ensayos-fundamentales-sobre-como-internet-esta-cambiando-nuestras-vidas/

Yepes Vélez, A., López Batista V. y Moreno, M. (2019). Sistema de Recomendación de música Sensible al Contexto. Avances en Informática y Automática. Duodécimo Workshop (pp. 40-64). https://gredos.usal.es/handle/10366/139439

Published

2021-06-28

How to Cite

Bazzara, L. (2021). Of funnels, filters and compasses: Economy, technique and subjectivity in Spotify. Hipertextos, 9(15), 47–82. https://doi.org/10.24215/23143924e028

Issue

Section

Artículos