What we think a person's playlist says about them: Inferred stereotypes based on music preferences
dc.contributor.author | Busick, Cortney Danielle | en |
dc.contributor.committeechair | Hernandez, Jorge Ivan | en |
dc.contributor.committeemember | Calderwood, Charles | en |
dc.contributor.committeemember | Savla, Jyoti Shital | en |
dc.contributor.committeemember | Diana, Rachel A. | en |
dc.contributor.department | Psychology | en |
dc.date.accessioned | 2025-05-28T08:04:32Z | en |
dc.date.available | 2025-05-28T08:04:32Z | en |
dc.date.issued | 2025-05-27 | en |
dc.description.abstract | This study demonstrates that music can be a proxy for understanding activation of a variety of stereotypes. These stereotypes also align with stereotypes in particular contexts like the workplace. Consequently, this study shows that there may be methods beyond typical self-report measures that can highlight psychological constructs of interest in research. While these methods may not entirely replace self-report, they can support an effort toward research that uses mixed methods for collecting data on particular constructs. Future research should examine this phenomenon in samples of different age groups, with other psychological constructs, and with other kinds of data in different contexts. | en |
dc.description.abstractgeneral | This study shows that music can be an indirect avenue for understanding how a variety of stereotypes are activated. These stereotypes also align with stereotypes in particular contexts like the workplace. As such, this study demonstrates that there may be methods beyond typical self-report measures (e.g., filling out a survey) that can highlight psychological constructs of interest in research. While these methods may not entirely replace self-report measures, they can support an effort toward research that uses mixed methods for collecting data on particular constructs. Future research should examine this phenomenon in samples of different age groups, with other psychological constructs, and with other kinds of data in different contexts. | en |
dc.description.degree | Doctor of Philosophy | en |
dc.format.medium | ETD | en |
dc.identifier.other | vt_gsexam:43746 | en |
dc.identifier.uri | https://hdl.handle.net/10919/134261 | en |
dc.language.iso | en | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | music | en |
dc.subject | mixed method | en |
dc.subject | Spotify API | en |
dc.subject | stereotypes | en |
dc.subject | stereotype activation | en |
dc.subject | workplace stereotypes | en |
dc.title | What we think a person's playlist says about them: Inferred stereotypes based on music preferences | en |
dc.type | Dissertation | en |
thesis.degree.discipline | Psychology | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | doctoral | en |
thesis.degree.name | Doctor of Philosophy | en |