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Using Machine Learning Methods for Data Analysis on Music Platforms

Student: Anastasiia Meshkova

Supervisor: Tatiana Yakushkina

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2020

In these latter days, music streaming platforms (services) have become the most popular method of listening to music. Streaming services offer consumers unlimited access to large music catalogs. The development of music streaming technology has made it possible for every artist to be independent and release music without anyone's support. Music streaming services allow listeners to discover new artists, and artists - to be noticed. Since music streaming services are the main platform for providing access to songs, every artist wants to bring their music product to more listeners and make it popular. The analysis of the technical characteristics provided by the streaming platform has shown which parameter values predominate among the most popular songs on this streaming service, and the predictive model created using the machine learning method allows artists to predict the value of the song's popularity on the service. Thus, the combination of the recommendations obtained from the analysis with the resulting predictive model will allow artists to predict the value of the popularity of their music composition, as well as find combinations of technical characteristics of the song that will bring the song more success on the streaming platform.

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