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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