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Computer Science > Distributed, Parallel, and Cluster Computing

arXiv:2108.02370 (cs)
[Submitted on 5 Aug 2021]

Title:Spotify Danceability and Popularity Analysis using SAP

Authors:Virginia Ochi, Ricardo Estrada, Teezal Gaji, Wendy Gadea, Emily Duong
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Abstract:Our analysis reviews and visualizes the audio features and popularity of songs streamed on Spotify*. Our dataset, downloaded from Kaggle and originally sourced from Spotify API, consists of multiple Excel files containing information relevant to our visualization and regression analysis. The exercise seeks to determine the connection between the popularity of the songs and the danceability. Insights to be included and factored as part of our analysis include song energy, valence, BPM, release date, and year.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Machine Learning (cs.LG); Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2108.02370 [cs.DC]
  (or arXiv:2108.02370v1 [cs.DC] for this version)
  https://doi.org/10.48550/arXiv.2108.02370

Submission history

From: Virginia Frazee [view email]
[v1] Thu, 5 Aug 2021 05:02:24 UTC (1,153 KB)
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