Predicting Musical Sophistication from Music Listening Behaviors: A Preliminary Study
August 22, 2018 Β· Declared Dead Β· π ACM Conference on Recommender Systems
"No code URL or promise found in abstract"
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Authors
Bruce Ferwerda, Mark Graus
arXiv ID
1808.07314
Category
cs.IR: Information Retrieval
Cross-listed
cs.HC,
cs.LG
Citations
10
Venue
ACM Conference on Recommender Systems
Last Checked
4 months ago
Abstract
Psychological models are increasingly being used to explain online behavioral traces. Aside from the commonly used personality traits as a general user model, more domain dependent models are gaining attention. The use of domain dependent psychological models allows for more fine-grained identification of behaviors and provide a deeper understanding behind the occurrence of those behaviors. Understanding behaviors based on psychological models can provide an advantage over data-driven approaches. For example, relying on psychological models allow for ways to personalize when data is scarce. In this preliminary work we look at the relation between users' musical sophistication and their online music listening behaviors and to what extent we can successfully predict musical sophistication. An analysis of data from a study with 61 participants shows that listening behaviors can successfully be used to infer users' musical sophistication.
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