The document describes a study that examined correlations between personality traits and preferences for different types of digital concert program notes. Researchers conducted an online study with 165 participants to analyze how the Big Five personality dimensions and levels of music background related to ratings of content consumption, interestingness, and novelty for various program note formats (varying text, audio, images, length). Results found correlations between certain personality traits like Openness and content preferences, and that personality and music background explained variance in preferences. The goal is to develop personalized and adaptive digital program notes based on inferred user personality and music interest.

1. Personality Correlates for Digital
Concert Program Notes
Marko Tkalčič, Bruce Ferwerda,
David Hauger, Markus Schedl
marko.tkalcic@jku.at http://cp.jku.at
UMAP 2015, Dublin
[ SHORT PAPER ]

2. Presentation Outline
• Big Picture
• Problem statement
• Experiment
• Results
• Conclusion
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Tkalcic et al., Personality Correlations for
Digital Concert Program Notes

3. Big picture
• FP7 project Phenicx http://phenicx.upf.edu/
• Classical music concerts
– Audio analysis
– Mobile application
– User modeling
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4. Big picture
• FP7 project Phenicx http://phenicx.upf.edu/
• Classical music concerts
– Audio analysis
– Mobile application
– User modeling
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5. Big picture
• FP7 project Phenicx http://phenicx.upf.edu/
• Classical music concerts
– Audio analysis
– Mobile application
– User modeling
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Digital Concert Program Notes
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6. Classical Music Concerts
• Classical music people are conservative
(technology)
• Nevertheless, just as opera subtitles ...
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7. Classical Music Concerts
• Classical music people are conservative
(technology)
• Nevertheless, just as opera subtitles ...
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8. Problem statement
• Personalized music information retrieval
• Problem:
• Concerts are rare
• Classical music lovers are knowledgeable
• They don‘t share informatoin online (massively)
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CLASSICAL MUSIC CONCERT-
GOERS KNOW EVERYTHING

9. Question
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WHAT IS THERE TO
PERSONALIZE?

10. Answer
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PROGRAM NOTES

11. Answer
Automatically generated, tailor-made multimedia content
offered to prospective audience members, introducing the
concert that will take place with the purpose of informing,
educating and pre-engaging users, supporting concert
anticipation.
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Digital Concert Program Notes
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PROGRAM NOTES

12. Program notes
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13. Usage Scenario
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Login – social
media account
Infer personal
characteristics -
personality
Social
media
traces
Adapt content
to the user
Supporting
MM
material
Adapted
content

14. Inference of personality
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Digital Concert Program Notes
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Login – social
media account
Infer personal
characteristics -
personality
Social
media
traces
Adapt content
to the user
Supporting
MM
material
Adapted
content
• Big5 personality model:
• Openness
• Conscientiousness
• Extraversion
• Agreeableness
• Neuroticism
• Correlates with music
preferences (Rentfrow et
al., 2003)

15. Inference of personality
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Login – social
media account
Infer personal
characteristics -
personality
Social
media
traces
Adapt content
to the user
Supporting
MM
material
Adapted
content
• Twitter (Quercia et al.,
2011)
• Facebook (Kosinski et al.,
2013)
• Instagram (Ferwerda et al.,
under review)
• Facebook disclosure
(Ferwerda et al., under
review)

16. Usage Scenario
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Digital Concert Program Notes
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Login – social
media account
Infer personal
characteristics -
personality
Social
media
traces
Adapt content
to the user
Supporting
MM
material
Adapted
content

17. Experiment
• Correlations between personality and content preferences
• AMT online study: 165 participants (93 females, age MD 37,
SD 72), within subject design
• Variables:
– IV: Musical background
– IV: Personality
– IV: Genre preferences
– DV: Content ratings (consumption/interestingness/novelty)
• Content (14 combinations) - Debussy: La Mer
– Text/audio/images
– Long/short
– Composer/performer/piece
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18. Results (1): personality vs. music
background
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19. Results (2): personality vs. classical
music
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20. Results (3)
• (O, C, A, E) positive correlation with
(consumption, interestingness, novelty)
• N negative correlation with (consumption,
interestingness, novelty)
• Music background positive correlation with
(consumption, interestingness, novelty)
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21. Results (3): neuroticism vs.
interestingness (performer-text-long)
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22. Results (3): openness vs.
interestingness (piece-text-short)
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23. Conclusion
• Personality & musical background account for
preverences variance
• Future work:
– Music background -> Goldsmiths MSI
– Automatic inference of MSI?
– ML for recommending content
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24. Thank you.
Marko Tkalčič, Bruce Ferwerda,
David Hauger, Markus Schedl
marko.tkalcic@jku.at http://cp.jku.at
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25. Results (3): agreeableness vs.
consumption (piece-audio-long)
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26. Results (3): conscientiousness vs.
consumption (orchestra-text-long)
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27. Music background questionnaire
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28. Recommender system
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29. Openness vs. Music background
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30. Openness vs. Classical music genre
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31. Agreeableness/Openness Vs. religious
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