![[PDF]](/pb-assets/Icons/adobe-pdf-icon-1498649896243.png){kind=icon}
Abstract
Research suggests that musical preferences are linked to personality, but this research has been hindered by genre-based theories and methods. We address this limitation using a novel method based on the actual attributes that people perceive from music. In Study 1, using 102 musical pieces representing 26 genres and subgenres, we show that 38 perceived attributes in music can be organized into three basic dimensions: arousal, valence, and depth. In Study 2 (N = 9,454), we show that people’s preferences for these musical attributes reflected their self-ratings of personality traits. Importantly, personality was found to predict musical preferences above and beyond demographic variables. These findings advance previous theory and research and have direct applications for the music industry, recommendation algorithms, and health-care professionals.
References
|
Bonneville-Roussy, A., Rentfrow, P. J., Xu, M. K., Potter, J. (2013). Music through the ages: Trends in musical engagement and preferences from adolescence through middle adulthood. Journal of Personality and Social Psychology, 105, 703. Google Scholar | Crossref | Medline | ISI | |
|
Brown, R. A. (2012). Music preferences and personality among Japanese university students. International Journal of Psychology, 47, 259–268. Google Scholar | Crossref | Medline | ISI | |
|
Buss, D. M. (1987). Selection, evocation, and manipulation. Journal of Personality and Social Psychology, 53, 1214–1221. Google Scholar | Crossref | Medline | ISI | |
|
Cattell, R. B., Anderson, J. C. (1953). The measurement of personality and behavior disorders by the I.P.A.T. music preference test. Journal of Applied Psychology, 37, 446–454. Google Scholar | Crossref | ISI | |
|
Cattell, R. B., Saunders, D. R. (1954). Musical preferences and personality diagnosis: A factorization of one hundred and twenty themes. Journal of Social Psychology, 39, 3–24. Google Scholar | Crossref | ISI | |
|
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates. Google Scholar | |
|
Costa, P. T., McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources. Google Scholar | |
|
Delsing, M. J. M. H., ter Bogt, T. F. M., Engels, R. C. M. E., Meeus, W. H. J. (2008). Adolescents’ music preferences and personality characteristics. European Journal of Personality, 22, 109–130. Google Scholar | Crossref | ISI | |
|
Dunn, P. G., de Ruyter, B., Bouwhuis, D. G. (2011). Toward a better understanding of the relation between music preference, listening behavior, and personality. Psychology of Music, 40, 411–428. Google Scholar | SAGE Journals | ISI | |
|
George, D., Stickle, K., Rachid, F., Wopnford, A. (2007). The association between types of music enjoyed and cognitive, behavioral, and personality factors of those who listen. Psychomusicology, 19, 32–56. Google Scholar | Crossref | |
|
Goldberg, L. R. (2006). Doing it all bass-ackwards: The development of hierarchical factor structures from the top down. Journal of Research in Personality, 40, 347–358. Google Scholar | Crossref | ISI | |
|
Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., Gough, H. G. (2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in Personality, 40, 84–96. Google Scholar | Crossref | ISI | |
|
Gosling, S. D., Rentfrow, P. J., Swann, W. B. (2003). A very brief measure of the Big Five personality domains. Journal of Research in Personality, 37, 504–528. Google Scholar | Crossref | ISI | |
|
Ioannidis, J. P. (2008). Why most discovered true associations are inflated. Epidemiology, 19, 640–648. Google Scholar | Crossref | Medline | ISI | |
|
Kosinski, M., Matz, S. C., Gosling, S. D., Popov, V., Stillwell, D. (2015). Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines. American Psychologist, 70, 543. Google Scholar | Crossref | Medline | ISI | |
|
Kosinski, M., Stillwell, D., Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110, 5802–5805. Google Scholar | Crossref | Medline | ISI | |
|
Langmeyer, A., Guglhör-Rudan, A., Tarnai, C. (2012). What do music preferences reveal about personality? A cross-cultural replication using self-ratings and ratings of music samples. Journal of Individual Differences, 33, 119–130. Google Scholar | Crossref | ISI | |
|
Levitin, D. J., Schaaf, A., Goldberg, L. R. (2005). Factor diagrammer (Version 1.1b) [computer software]. Montreal, Canada: McGill University. Retrieved from http://daniellevitin.com/levitinlab/LabWebsite/software/factor_diagrammer/ Google Scholar | |
|
Rawlings, D., Barrantes-Vidal, N., Furnham, A. (2000). Personality and aesthetic preference in Spain and England: Two studies relating sensation seeking and openness to experience to liking for paintings and music. European Journal of Personality, 14, 553–576. Google Scholar | Crossref | ISI | |
|
Rentfrow, P. J. (2012). The role of music in everyday life: Current directions in the social psychology of music. Social and Personality Psychology Compass, 6, 402–416. Google Scholar | Crossref | |
|
Rentfrow, P. J., Goldberg, L. R., Levitin, D. J. (2011). The structure of musical preferences: A five-factor model. Journal of Personality and Social Psychology, 100, 1139–1157. Google Scholar | Crossref | Medline | ISI | |
|
Rentfrow, P. J., Goldberg, L. R., Stillwell, D. J., Kosinski, M., Gosling, S. D., Levitin, D. J. (2012). The song remains the same: A replication and extension of the MUSIC model. Music Perception, 30, 161–185. Google Scholar | Crossref | Medline | ISI | |
|
Rentfrow, P. J., Gosling, S. D. (2003). The do re mi’s of everyday life: The structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84, 1236–1256. Google Scholar | Crossref | Medline | ISI | |
|
Rentfrow, P. J., McDonald, J. A. (2009). Music preferences and personality. In Juslin, P. N., Sloboda, J. (Eds.), Handbook of music and emotion (pp. 669–695). Oxford, England: Oxford University Press. Google Scholar | |
|
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178. Google Scholar | Crossref | ISI | |
|
Schönbrodt, F. D., Perugini, M. (2013). At what sample size do correlations stabilize? Journal of Research in Personality, 47 (5), 609–612. Google Scholar | Crossref | ISI | |
|
Swann, W. B., Rentfrow, P. J., Guinn, J. S. (2002). Self-verification: The search for coherence. In Leary, M., Tagney, J. (Eds.) Handbook of self and identity (pp. 367–383). New York, NY: Guilford Press. Google Scholar | |
|
van der Heijden, M. J., Araghi, S. O., van Dijk, M., Jeekel, J., Hunink, M. M. (2015). The effects of perioperative music interventions in pediatric surgery: A systematic review and meta-analysis of randomized controlled trials. PloS One, 10, e0133608. Google Scholar | Crossref | ISI | |
|
Vuoskoski, J. K., Thompson, W. F., McIlwain, D., Eerola, T. (2012). Who enjoys listening to sad music and why? Music Perception, 29, 311–317. Google Scholar | Crossref | ISI | |
|
Watson, D., Clark, L. A., Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063. Google Scholar | Crossref | Medline | ISI | |
|
Zweigenhaft, R. L. (2008). A do re mi encore: A closer look at the personality correlates of music preferences. Journal of Individual Differences, 29, 45–55. Google Scholar | Crossref | ISI |
