2020
DOI: 10.1177/0305735620953611
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Influence of personality on music-genre exclusivity

Abstract: Studies reveal consistent relationships between personality and preferred musical genre. This article explores these relationships using a novel methodology: genre dispersion among people’s mobile-phone music collections. By analyzing the download behavior of genre-based user subgroups, we investigated the following questions: (1) do genre-based subgroups exhibit different levels of genre exclusivity; and (2) does genre exclusivity relate to Big Five personality factors? We hypothesized that genre-based subgro… Show more

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Cited by 13 publications
(8 citation statements)
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References 35 publications
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“…Dunn et al (2012) measured self-reported preferences and analyzed listening behavior from a music streaming database over a 3-month period. Their results showed a positive correlation between these two measures, an important finding that supports the validity of existing research (that used self-report measures of music preference) and inferences made in studies, such as that of Bansal, Flannery, and Woolhouse (2020), who deduced musical preference based on user’s music collections.…”
Section: Introductionsupporting
confidence: 71%
See 1 more Smart Citation
“…Dunn et al (2012) measured self-reported preferences and analyzed listening behavior from a music streaming database over a 3-month period. Their results showed a positive correlation between these two measures, an important finding that supports the validity of existing research (that used self-report measures of music preference) and inferences made in studies, such as that of Bansal, Flannery, and Woolhouse (2020), who deduced musical preference based on user’s music collections.…”
Section: Introductionsupporting
confidence: 71%
“…Openness was an additional factor in Bansal et al (2020) that positively correlated to breadth of musical taste. In our study, openness related to higher ratings of stimuli with piano dynamics and of Bach and Beethoven piece .…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, when people extract the original features of music signals, they mainly extract short-term features. There are three types of short-time features ( Bansal et al, 2021 ). The music feature time domain is a kind of parameter feature, and it is directly extracted from the time-domain waveform of the music signal.…”
Section: Methodsmentioning
confidence: 99%
“…Various metadata about users are also housed in the database, including user ID, total number of downloads and user country. Because of its size and the nature of the data it contains, the database is an excellent tool for cultural and social investigations relating to music [23][24][25][26].…”
Section: Description Of the Datamentioning
confidence: 99%