The rhythm of Mexico: an exploratory data analysis of Spotify’s top 50
| Autor: | J. Manuel Pérez-Verdejo, L. Méndez-Morales, C. A. Piña-García, A. Rivera-Lara, Mario Miguel Ojeda |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science Big data 02 engineering and technology Track (rail transport) World Wide Web Exploratory data analysis Chart 020204 information systems 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing Social media Computational linguistics business Digital audio |
| Zdroj: | Journal of Computational Social Science. 4:147-161 |
| ISSN: | 2432-2725 2432-2717 |
| DOI: | 10.1007/s42001-020-00070-z |
| Popis: | Spotify has emerged as an important online platform for streaming digital music. A key aspect of Spotify is that it provides access to music on-demand to a worldwide level. In this regard, Spotify via its API permits to gain access to music-related data with the aim to know information about different parameters such as: artist, album, and genre. This paper aims to: (1) give an overview of the shared features of the songs that appeared at Mexico’s top 50 during 2019, (2) analyze how these features are related to a track permanence on the top 50; and (3) compare those results with the global top 50 chart. |
| Databáze: | OpenAIRE |
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