Cluster Analysis of Musical Attributes for Top Trending Songs

Date
2020-01-07
Authors
Al-Beitawi , Zayd
Salehan, Mohammad
Zhang, Sonya
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Music streaming services like Spotify have changed the way consumers listen to music. Understanding what attributes make certain songs trendy can help services to create a better customer experience as well as more effective marketing efforts. We performed cluster analysis on Top 100 Trending Spotify Song of 2017, with ten attributes, including danceability, energy, loudness, speechiness, acousticness, instrumentalness, Liveness, valence, tempo, and duration. The results show that music structures with high danceability and low instrumentalness increase the popularity of a song and lead them to chart-topping success.
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AI and Cognitive Assistants in Collaboration, clustering, music streaming, recommender systems
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7 pages
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Proceedings of the 53rd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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