Conference proceeding
Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior
15TH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS 2021), pp 639-644
01 Jan 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
Metrics
Details
- Title
- Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior
- Creators
- Lawrence Spear - Boise State UniversityAshlee Milton - Boise State UniversityGarrett Allen - Boise State UniversityAmifa Raj - Boise State UniversityMichael Green - Boise State UniversityMichael D. Ekstrand - Boise State UniversityMaria Soledad Pera - Boise State UniversityACM
- Publication Details
- 15TH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS 2021), pp 639-644
- Publisher
- Assoc Computing Machinery
- Number of pages
- 6
- Grant note
- 1763649; 1751278; 1930464 / NSF; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000744461300084
- Scopus ID
- 2-s2.0-85115639451
- Other Identifier
- 991021818497204721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems