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Full-Text Articles in Music Business
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
SMU Data Science Review
Abstract. Over 87% of the streaming music is owned by four major record labels (Jones, 2018). Yet, the songs owned by those labels account for <1% of the total amount of music created each year. These labels are historically better at identifying talent (though this talent identification is becoming more difficult). Even though Spotify has 36% of the streaming marketing share (T4, 2021), Spotify has not been profitable because of the large licensing costs paid to the large music labels. If Spotify could identify hit songs & artists before the large labels, they would sign those artists and dramatically reduce their licensing costs. Using the Spotify API, this paper will use Spotify data on over 400K songs over the last three years for exploratory data analysis, provide descriptive statistics, perform feature selection, and develop models using LASSO and XGBOOST Classification. The research determined multiple key features and predicted with over 60% accuracy songs which were going to be a hit (defined as >90% popularity).
The Supply Chain Of Digital Music: Empowering Independent Artists Through Availability And Accessibility, Justin Reed
The Supply Chain Of Digital Music: Empowering Independent Artists Through Availability And Accessibility, Justin Reed
Senior Theses
The process of creating and sharing digital music can be viewed from the “supply chain” perspective: identifying the resources and value-adding tools that ultimately result in a final audio product. By researching and documenting the steps involved in this process, I identify this supply chain as a series of steps, an itinerary, or process model of digital music creation. Moreover, I found that each step in the process can be assess for its accessibility and usability by independent artists. I conclude by exploring how this democratizes the music industry by affording independent artists the necessary tools and empowerment to create …
International Music Preferences: An Analysis Of The Determinants Of Song Popularity On Spotify For The U.S., Norway, Taiwan, Ecuador, And Costa Rica, Brendan Joseph Suh
International Music Preferences: An Analysis Of The Determinants Of Song Popularity On Spotify For The U.S., Norway, Taiwan, Ecuador, And Costa Rica, Brendan Joseph Suh
CMC Senior Theses
This paper examines data from Spotify’s API for 2017-2018 to determine the effects of song attributes on the success of tracks on Spotify’s Top 200 Chart across five different countries: the U.S., Norway, Taiwan, Ecuador, and Costa Rica. Two dependent variables are used to measure the success of a song – a track’s peak position on the charts and the number of days it survives on a country’s Top 200 Chart. Using ten separate regressions, one for each dependent variable in all five countries, it is concluded that the presence of a featured guest on a track increases a song’s …