Algorithmic Personalization in Consumption of On Demand Content: an analysis of Spotify® patents

Spotify® uses data mining and profiling to provide a personalized experience for its users. This study analyzes Spotify® patent applications related to algorithmic user experience personalization. Using Questel Orbit Intelligence®, 18 patent applications were identified, grouped into three categorie...

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Bibliographic Details
Authors: Souza, Rafael Rodrigues de, Fujita, Allynson Takehiro, Meireles, Eduardo
Format: article
Status:Published version
Publication Date:2024
Country:Brasil
Institution:Universidade Federal da Bahia (UFBA)
Repository:Cadernos de Prospecção (Online)
Language:Portuguese
OAI Identifier:oai:ojs.periodicos.ufba.br:article/56107
Online Access:https://periodicos.ufba.br/index.php/nit/article/view/56107
Access Level:Open access
Keyword:Streaming
Personalização algorítmica
Recomendação de conteúdo.
Algorithmic customization
Content recommendation.
Description
Summary:Spotify® uses data mining and profiling to provide a personalized experience for its users. This study analyzes Spotify® patent applications related to algorithmic user experience personalization. Using Questel Orbit Intelligence®, 18 patent applications were identified, grouped into three categories. The first addresses technical criteria for recommendations, the second focuses on users' subjective preferences, while the third presents distinct characteristics. These requests reflect Spotify®'s efforts to provide a personalized experience, including suggesting content through algorithmic means. Some requests suggest personalizing ads based on predictions of users' mood and location. This analysis confirms the presence of algorithmic personalization on the platform and highlights concerns about the serving of advertisements, in addition to the ethical limits of the use of artificial intelligence, indicating the need for regulation to mitigate possible risks to consumers or the creative industry.