Musical Preference: Role of Personality and Music-Related Acoustic Features

Abstract

Personality factors, typically determined by the Big Five Inventory (BFI), have been a primary method for investigating individual preferences in music. While these studies have yielded a number of insights into musical choices, weaknesses exist, owing to the methods by which music is characterized and categorized. For example, musical genre, music-preference dimensions (e.g., reflective and complex), and musical attributes (e.g., strong and mellow), reported within the literature, have arguably produced inconsistent and thus difficult to interpret results. We attempt to circumvent these inconsistencies by classifying music using objectively quantifiable acoustic features that are fundamental to Western music, such as tempo and register. Moreover, it is our contention that the link between musical preference and personality may operate primarily at the level of acoustic features and not at broader categorization levels, such as genre. This study attempts to address this issue. Ninety participants listened to and indicated preference for stimuli that were systematically manipulated by dynamics (attack rate), mode, register, and tempo. Personality was measured using the BFI, allowing for analysis of personality traits and preference for acoustic features. Results supported the link between personality and preference for certain acoustic features. Preference with respect to dynamics was related to openness and extraversion; mode to conscientiousness and extraversion; register to extraversion and neuroticism; and tempo to conscientiousness, extraversion, and neuroticism. Though significant, these associations were relatively weak; therefore, future research could expand the number of manipulated acoustic features. Specific attempts should also aim to disentangle the effects of genre versus acoustic features on musical preferences. Personality–preference relationships at the acoustic-feature level are discussed with respect to music recommender systems and other aspects of the literature.

Personality Computing With Naturalistic Music Listening Behavior: Comparing Audio and Lyrics Preferences

“…However, a meta-analysis on the correlation between musical style preferences and personality concluded that the effect sizes for Openness were only small, and the remaining Big Five dimensions exhibited inconsistent or no associations in this line of music research (Schäfer & Mehlhorn, 2017). These findings may relate, at least in part, to the high degree of abstraction in past studies measuring music preferences via broad genre and style categorizations, which lack a distinct definition by musical properties and, thus, prevent conclusions about the aspects of music relating to personality dimensions (Aucouturier & Pachet, 2003;Flannery & Woolhouse, 2021;Rentfrow et al, 2011). Specifically, genre preferences contain inconsistent meta-information about the preferred music, like the music's geographical origin (e.g., Latin), its popularity (e.g., Pop), or stereotypes associated with the music's fans (e.g., Punk; Rentfrow & Gosling, 2007).…”

“…Only a few pioneer studies have assessed preferences for individual audio characteristics and revealed differential associations with the Big Five personality traits. Thereby, Openness was correlated to preferences for slow tempo, minor mode, acoustic sounds, and negative valence, while Extraversion was related to preferences for major mode, high tones, and positive valence (Dobrota & Reić Ercegovac, 2017;Flannery & Woolhouse, 2021;Fricke & Herzberg, 2017;Vuoskoski & Eerola, 2011).…”

“…First, the ecological validity was limited in past work because music listening behavior could only be measured via self-reports (e.g., Rentfrow & Gosling, 2003;North et al, 2000) or ratings of music excerpts (e.g., Flannery & Woolhouse, 2021;Nave et al, 2018).…”

“…Second, past research had to rely on human labeling instead of objective metrics to quantify preferences for musical attributes (i.e., audio and lyrics characteristics; e.g., Burke & Grinder, 1966;Rentfrow et al, 2011;Dobrota & Reić Ercegovac, 2017). Only the latest studies in the field assessed musical characteristics that were extracted automatically from audio recordings or song lyrics (Anderson et al, 2021;Flannery & Woolhouse, 2021;Stachl et al, 2020;Qiu et al, 2019). While technical audio characteristics can now be obtained in a ready-to-use format from external sources (e.g., Spotify, 2022) or via music analysis software (e.g., ESSENTIA; s. Fricke et al, 2018), textual lyrical characteristics must be extracted via natural language processing (NLP).…”

A correlation study of music training, adult attachment, and personality traits using a large-sample questionnaire

“…The dynamic two-way interaction between music training and personality has become the focus of psychological research in recent years. On the one hand, personality characteristics can affect individuals’ music preferences ( Flannery and Woolhouse, 2021 ), music-induced movement or dancing style ( Luck et al, 2010 ), and the durability and effectiveness of music training ( Swaminathan and Schellenberg, 2018 ) across different ages ( Luo et al, 2014 ). On the other hand, music training can improve the personality characteristics of individuals.…”