2020
DOI: 10.22456/2175-2745.107021
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A Model for Predicting Music Popularity on Streaming Platforms

Abstract: The global music market moves billions of dollars every year, most of which comes from streamingplatforms. In this paper, we present a model for predicting whether or not a song will appear in Spotify’s Top 50, a ranking of the 50 most popular songs in Spotify, which is one of today’s biggest streaming services. To make this prediction, we trained different classifiers with information from audio features from songs that appeared in this ranking between November 2018 and January 2019. When tested with data fro… Show more

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Cited by 6 publications
(2 citation statements)
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References 11 publications
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“…Reference [28] evaluated the potential of songs on streaming platforms to become viral and sustain popularity. Reference [29] used classifiers to predict the presence of songs in Spotify's Top-50, focusing on audio features. Reference [30] introduced a new dataset and deep learning architecture for predicting music popularity.…”
Section: Related Workmentioning
confidence: 99%
“…Reference [28] evaluated the potential of songs on streaming platforms to become viral and sustain popularity. Reference [29] used classifiers to predict the presence of songs in Spotify's Top-50, focusing on audio features. Reference [30] introduced a new dataset and deep learning architecture for predicting music popularity.…”
Section: Related Workmentioning
confidence: 99%
“…Evaluasi eksperimental didasarkan pada validasi (80 persen untuk pelatihan dan 20 persen untuk pengujian) dengan akurasi maksimum 60,17 persen, diperoleh dari Gaussian Naïve Bayes. Penelitian lain yang mendukung penelitian ini adalah penelitian yang diusulkan di studi [8].…”
Section: Kajian Pustakaunclassified