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[journal article]

dc.contributor.authorAl Baghal, Tarekde
dc.contributor.authorSloan, Lukede
dc.contributor.authorJessop, Curtisde
dc.contributor.authorWilliams, Matthew L.de
dc.contributor.authorBurnap, Petede
dc.date.accessioned2023-02-01T12:36:38Z
dc.date.available2023-02-01T12:36:38Z
dc.date.issued2020de
dc.identifier.issn1552-8286de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/85012
dc.description.abstractIn light of issues such as increasing unit nonresponse in surveys, several studies argue that social media sources such as Twitter can be used as a viable alternative. However, there are also a number of shortcomings with Twitter data such as questions about its representativeness of the wider population and the inability to validate whose data you are collecting. A useful way forward could be to combine survey and Twitter data to supplement and improve both. To do so, consent within a survey is first needed. This study explores the consent decisions in three large representative surveys of the adult British population to link Twitter data to survey responses and the impact that demographics and survey mode have on these outcomes. Findings suggest that consent rates for data linkage are relatively low, and this is in part mediated by mode, where face-to-face surveys have higher consent rates than web versions. These findings are important to understand the potential for linking Twitter and survey data but also to the consent literature generally.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherconsent; linkage; mode effectsde
dc.titleLinking Twitter and Survey Data: The Impact of Survey Mode and Demographics on Consent Rates Across Three UK Studiesde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.identifier.urllocalfile:/var/tmp/crawlerFiles/deepGreen/b066088ef5154999902408402313849b/b066088ef5154999902408402313849b.pdfde
dc.source.journalSocial Science Computer Review
dc.source.volume38de
dc.publisher.countryUSAde
dc.source.issue5de
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozUmfrageforschungde
dc.subject.thesozsurvey researchen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozBefragungde
dc.subject.thesozsurveyen
dc.subject.thesozTwitterde
dc.subject.thesoztwitteren
dc.subject.thesozSoziale Mediende
dc.subject.thesozsocial mediaen
dc.subject.thesozAntwortverhaltende
dc.subject.thesozresponse behavioren
dc.subject.thesozDatenqualitätde
dc.subject.thesozdata qualityen
dc.subject.thesozRepräsentativitätde
dc.subject.thesozrepresentativityen
dc.identifier.urnurn:nbn:de:0168-ssoar-85012-3
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10040714
internal.identifier.thesoz10040547
internal.identifier.thesoz10037910
internal.identifier.thesoz10094030
internal.identifier.thesoz10094228
internal.identifier.thesoz10035808
internal.identifier.thesoz10055811
internal.identifier.thesoz10056653
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo517-532de
internal.identifier.classoz10105
internal.identifier.journal645
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1177/0894439319828011de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.dda.referencecrawler-deepgreen-188@@b066088ef5154999902408402313849b


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