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Title: Baby Shark to Barracuda: Analyzing Children’s Music Listening Behavior
Music is an important part of childhood development, with online music listening platforms being a significant channel by which children consume music. Children’s offline music listening behavior has been heavily researched, yet relatively few studies explore how their behavior manifests online. In this paper, we use data from LastFM 1 Billion and the Spotify API to explore online music listening behavior of children, ages 6–17, using education levels as lenses for our analysis. Understanding the music listening behavior of children can be used to inform the future design of recommender systems.
Authors:
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Award ID(s):
1751278
Publication Date:
NSF-PAR ID:
10316668
Journal Name:
Fifteenth ACM Conference on Recommender Systems
Sponsoring Org:
National Science Foundation
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