Decoding Spotify Audio Features Data: Helping Artists Utilize Big Tech-Optimizing Touring Using Valence and Algorithm
Decoding Spotify Audio Features Data: Helping Artists Utilize Big Tech-Optimizing Touring Using Valence and Algorithm
dc.contributor.author | Paul W. Zielenski | |
dc.date.accessioned | 2022-12-05T18:48:54Z | |
dc.date.available | 2022-12-05T18:48:54Z | |
dc.date.issued | 2022-12-01 | |
dc.description.abstract | Creating an initial “how to” for artists to access and understand the information available via the API would put them in a position to create a positive trajectory for themselves. This project has developed, tested and published a computer script capable of extracting and analyzing key data from the Spotify API’s musical valence algorithms. The project also explores using data to optimize live shows, discusses the benefits such exploration might provide for artists, and outlines possible later expansion of the script’s capabilities and uses. | |
dc.identifier.uri | https://jewlscholar.mtsu.edu/handle/mtsu/6775 | |
dc.language.iso | en_US | |
dc.publisher | College of Media and Entertainment, Middle Tennessee State University | |
dc.title | Decoding Spotify Audio Features Data: Helping Artists Utilize Big Tech-Optimizing Touring Using Valence and Algorithm | |
dc.type | Capstone | |
dspace.entity.type |
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