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Decoding cultural consumption from digital traces

dc.contributor.authorPark, Minsu
dc.contributor.chairMacy, Michael Walton
dc.contributor.committeeMemberNaaman, Mor
dc.contributor.committeeMemberMargolin, Drew
dc.date.accessioned2019-10-15T16:51:53Z
dc.date.available2019-10-15T16:51:53Z
dc.date.issued2019-08-30
dc.description.abstractWith an unprecedented scale of users interacting with online platforms and mobile devices, digital traces (i.e., detailed behavioral data generated from those sources) provide us with an unparalleled opportunity to explore new scientific approaches that enable novel insights about the patterns of cultural consumption, which has an impact on social and social-psychological outcomes. Through discussion of three projects, I show that by leveraging the large-scale digital traces (i) individuals manage mood through self-exposure to external stimuli such as music, e.g., people listen to more relaxing music late at night and more energetic music during normal business hours, including mid-afternoon when affective expression is lowest, (ii) cross-cultural convergence is more advanced in cosmopolitan countries with cultural values that favor individualism and power inequality, and (iii) the diversity of musical tastes are associated with whether one is following high-profile news media and how much one is 'into' music rather than socioeconomic covariates such as income and education.
dc.identifier.doihttps://doi.org/10.7298/4tc3-vk77
dc.identifier.otherPark_cornellgrad_0058F_11669
dc.identifier.otherhttp://dissertations.umi.com/cornellgrad:11669
dc.identifier.otherbibid: 11050775
dc.identifier.urihttps://hdl.handle.net/1813/67788
dc.language.isoen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPreference
dc.subjectculture
dc.subjectSocial Networks
dc.subjectSociology
dc.subjectconsumption
dc.subjectCommunication
dc.subjectInformation science
dc.titleDecoding cultural consumption from digital traces
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810
thesis.degree.disciplineInformation Science
thesis.degree.grantorCornell University
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh.D., Information Science

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