Investigating Music Track Liking in the Halo of Album Covers

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Research on music retrieval and recommendation often neglects the fact that a user's response to a music track depends on contextual factors, such as the composition of the results list, the design of the user interface or the additional media displayed. However, a body of psychological research suggests that human perception and decision making can be strongly influenced by contextual factors. In particular, an initial positive aesthetic impression of a product may influence a buyer's perception of its features unrelated to appearance, such as utility or reliability, which is a manifestation of a cognitive bias called the halo effect. The work at hand investigates whether an album cover shown to the listener during playback can create a halo effect, influencing the listener's liking of the track. We approach this question by means of a two-stage user study. In the first stage, participants individually rated a series of album covers and music snippets. In the second stage, they were presented with music tracks and album covers (from those they indicated as unfamiliar to them at the first stage) arranged in pairs, such that their least liked tracks were shown with their most liked album covers and vice versa. The results show that displaying an appealing album cover while playing a music track results in a higher rating of the track.
Original languageGerman (Austria)
Title of host publicationProceedings of the 26th ISMIR Conference
Number of pages8
Edition1
DOIs
Publication statusPublished - 2025

Fields of science

  • 102003 Image processing
  • 202002 Audiovisual media
  • 102001 Artificial intelligence
  • 102015 Information systems
  • 102 Computer Sciences
  • 101019 Stochastics
  • 103029 Statistical physics
  • 101018 Statistics
  • 101017 Game theory
  • 202017 Embedded systems
  • 101016 Optimisation
  • 101015 Operations research
  • 101014 Numerical mathematics
  • 101029 Mathematical statistics
  • 101028 Mathematical modelling
  • 101026 Time series analysis
  • 101024 Probability theory
  • 102032 Computational intelligence
  • 102004 Bioinformatics
  • 102013 Human-computer interaction
  • 101027 Dynamical systems
  • 305907 Medical statistics
  • 101004 Biomathematics
  • 305905 Medical informatics
  • 101031 Approximation theory
  • 102033 Data mining
  • 305901 Computer-aided diagnosis and therapy
  • 102019 Machine learning
  • 106007 Biostatistics
  • 102018 Artificial neural networks
  • 106005 Bioinformatics
  • 202037 Signal processing
  • 202036 Sensor systems
  • 202035 Robotics

JKU Focus areas

  • Digital Transformation

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