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The Music Industry in the Streaming Age: Predicting the Success of a Song on Spotify.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Music Industry in the Streaming Age: Predicting the Success of a Song on Spotify./
Author:	Matera, Matteo.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	32 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Contained By:	Dissertations Abstracts International83-12B.
Subject:	Application programming interface. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29097830
ISBN:	9798819343562

The Music Industry in the Streaming Age: Predicting the Success of a Song on Spotify.
Matera, Matteo.

The Music Industry in the Streaming Age: Predicting the Success of a Song on Spotify. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 32 p.

Source: Dissertations Abstracts International, Volume: 83-12, Section: B.

Thesis (M.M.)--Universidade NOVA de Lisboa (Portugal), 2021.

This item must not be sold to any third party vendors.

The digitization of information goods has fundamentally changed the consumption patterns of music, such that the music popularity has been redefined in the streaming era. Still, the production of hit music that captures the lion's share of music consumption remains the central focus of business operations in the music industry. This paper aims at building a machine learning model capable of predicting the success of songs on Spotify. The created dataset contains 14,303 songs some appeared in Spotify's Global Top 200 chart and others never entered in the chart. The problem was approached as a classification task and the best results were obtained by the Random Forest classifier with an F1 score of 85,6% on the validation set.

ISBN: 9798819343562Subjects--Topical Terms:

3562904
Application programming interface.

The Music Industry in the Streaming Age: Predicting the Success of a Song on Spotify.
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