Effects of algorithmic curation in users’ music taste on Spotify
DOI:
https://doi.org/10.23882/rmd.24258Palabras clave:
Spotify, algorithmic curation, digital platforms, calculated publics, taste, platformization, filter bubblesResumen
Este estudio aborda el impacto potencial de los algoritmos de recomendación en los gustos musicales de los usuarios de Spotify, con el objetivo de comprender cómo las sugerencias algorítmicas moldean los comportamientos y preferencias de escucha. Una revisión exhaustiva de la literatura revela que la presencia de algoritmos ha contribuido a la reducción de la diversidad musical y al aumento de la tautología de gustos entre los usuarios. Los resultados sugieren que los algoritmos de recomendación refuerzan preferencias anteriores, contribuyendo a la creación de filter bubbles. Este gusto impulsado por algoritmos tiene implicaciones culturales evidentes y, con ello, un gran impacto en la diversidad general de la experiencia musical. Se utilizó una metodología cualitativa, compuesta por una revisión sistemática de la literatura basada en el protocolo PRISMA, identificando tendencias y elementos clave de los estudios existentes. Este estudio encuentra sus limitaciones en la necesidad de un estudio cuantitativo adicional para profundizar en la comprensión del comportamiento de los algoritmos de recomendación. En última instancia, esta investigación resalta la necesidad de una mayor concienciación sobre las implicaciones de la recomendación musical a través de algoritmos en la era digital.
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Derechos de autor 2025 Marta Ezquerra Fernández
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
