Title

Cluster Analysis of Spotify Users

Presenter Information/ Coauthors Information

Audrey BungeFollow

Presentation Type

Poster

Student

Yes

Track

Other

Abstract

Spotify is considered one of the best music streaming providers in the world. Spotify users can access different information regarding not only tracks, albums, and artists, but also personal listening habits by using a lesser known Spotify feature, the Web Application Programming Interface. The personal listening habits obtained include the top 50 artists of all time, and the top 50 tracks of all time. Market basket analysis is used to condense the genres from the top 50 artists of all time per user. Following the use of each user’s top 50 artists and with some data manipulation, we conduct K-means cluster analysis on the 50 top tracks of all time for each user. Once clusters are obtained, we can identify similar listening habits among users.

Start Date

5-2-2019 12:00 PM

End Date

5-2-2019 1:00 PM

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Cluster Analysis of Spotify Users

Volstorff A

Spotify is considered one of the best music streaming providers in the world. Spotify users can access different information regarding not only tracks, albums, and artists, but also personal listening habits by using a lesser known Spotify feature, the Web Application Programming Interface. The personal listening habits obtained include the top 50 artists of all time, and the top 50 tracks of all time. Market basket analysis is used to condense the genres from the top 50 artists of all time per user. Following the use of each user’s top 50 artists and with some data manipulation, we conduct K-means cluster analysis on the 50 top tracks of all time for each user. Once clusters are obtained, we can identify similar listening habits among users.