The influence of personal values on music taste: Towards value-based music recommendations

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

The feld of recommender systems has a lot to gain from the feld of psychology. Indeed, many psychology researchers have investigated relations between models that describe humans and consumption preferences. One example of this is personality, which has been shown to be a valid construct to describe people. As a consequence, personality-based recommenders have already proven to be a lead toward improving recommendations, by adapting them to their users' traits. Beyond personality, there are more ways to describe a person's identity. One of these ways is to consider personal values: what is important for the users in life at the most abstract level. Being complementary to personality traits, values may give another lead towards better user understanding. In this paper, we investigate this, taking music as a use case. We use a marketing interview technique to elicit 22 users' personal values connected to their musical preferences. We show that personal values indeed play a role in people's music preferences, and are the frst to propose a map linking personal values to music preferences. We see this map as a frst step in devising a value-based user model for music recommender systems.

Original languageEnglish
Title of host publicationRecSys 2019 - 13th ACM Conference on Recommender Systems
Subtitle of host publicationProceedings of the 13th ACM Conference on Recommender Systems
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages501-505
Number of pages5
ISBN (Electronic)9781450362436
DOIs
Publication statusPublished - 10 Sept 2019
Event13th ACM Conference on Recommender Systems, RecSys 2019 - Copenhagen, Denmark
Duration: 16 Sept 201920 Sept 2019

Publication series

NameRecSys 2019 - 13th ACM Conference on Recommender Systems

Conference

Conference13th ACM Conference on Recommender Systems, RecSys 2019
Country/TerritoryDenmark
CityCopenhagen
Period16/09/1920/09/19

Keywords

  • Explainable Recommender Systems
  • Music Recommendations
  • Musical Taste
  • Novel Applications
  • Personal values
  • Psychology of Music
  • User Modelling
  • OA-Fund TU Delft

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