Decoding Spotify Audio Features Data: Helping Artists Utilize Big Tech-Optimizing Touring Using Valence and Algorithm

dc.contributor.authorPaul W. Zielenski
dc.date.accessioned2022-12-05T18:48:54Z
dc.date.available2022-12-05T18:48:54Z
dc.date.issued2022-12-01
dc.description.abstractCreating 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.urihttps://jewlscholar.mtsu.edu/handle/mtsu/6775
dc.language.isoen_US
dc.publisherCollege of Media and Entertainment, Middle Tennessee State University
dc.titleDecoding Spotify Audio Features Data: Helping Artists Utilize Big Tech-Optimizing Touring Using Valence and Algorithm
dc.typeCapstone
dspace.entity.type

Files

Original bundle

Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
Helping Artists Utilize Big Tech _ Optimizing Touring Using Valence and Algorithm.docx
Size:
817.34 KB
Format:
Microsoft Word XML
Loading...
Thumbnail Image
Name:
Decoding Spotify Audio Features Data (2).html
Size:
6.33 MB
Format:
Hypertext Markup Language

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.27 KB
Format:
Item-specific license agreed upon to submission
Description: