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[journal article]

dc.contributor.authorFraser, Nicholasde
dc.contributor.authorMomeni, Fakhride
dc.contributor.authorMayr, Philippde
dc.contributor.authorPeters, Isabellade
dc.date.accessioned2021-02-17T12:17:47Z
dc.date.available2021-02-17T12:17:47Z
dc.date.issued2020de
dc.identifier.issn2641-3337de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/71641
dc.description.abstractA potential motivation for scientists to deposit their scientific work as preprints is to enhance its citation or social impact. In this study we assessed the citation and altmetric advantage of bioRxiv, a preprint server for the biological sciences. We retrieved metadata of all bioRxiv preprints deposited between November 2013 and December 2017, and matched them to articles that were subsequently published in peer-reviewed journals. Citation data from Scopus and altmetric data from Altmetric.com were used to compare citation and online sharing behavior of bioRxiv preprints, their related journal articles, and nondeposited articles published in the same journals. We found that bioRxiv-deposited journal articles had sizably higher citation and altmetric counts compared to nondeposited articles. Regression analysis reveals that this advantage is not explained by multiple explanatory variables related to the articles' publication venues and authorship. Further research will be required to establish whether such an effect is causal in nature. bioRxiv preprints themselves are being directly cited in journal articles, regardless of whether the preprint has subsequently been published in a journal. bioRxiv preprints are also shared widely on Twitter and in blogs, but remain relatively scarce in mainstream media and Wikipedia articles, in comparison to peer-reviewed journal articles.de
dc.languageende
dc.subject.ddcPublizistische Medien, Journalismus,Verlagswesende
dc.subject.ddcNews media, journalism, publishingen
dc.subject.otheraltmetrics; bioRxiv; citation advantage; citations; preprintsde
dc.titleThe relationship between bioRxiv preprints, citations and altmetricsde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalQuantitative Science Studies
dc.source.volume1de
dc.publisher.countryUSA
dc.source.issue2de
dc.subject.classozSzientometrie, Bibliometrie, Informetriede
dc.subject.classozScientometrics, Bibliometrics, Informetricsen
dc.subject.thesozScientometriede
dc.subject.thesozscientometryen
dc.subject.thesozWissenschaftsforschungde
dc.subject.thesozscience studiesen
dc.subject.thesozPublikationde
dc.subject.thesozpublicationen
dc.subject.thesozPeer Reviewde
dc.subject.thesozpeer reviewen
dc.subject.thesozRegressionsanalysede
dc.subject.thesozregression analysisen
dc.identifier.urnurn:nbn:de:0168-ssoar-71641-8
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionGESISde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10064428
internal.identifier.thesoz10062541
internal.identifier.thesoz10041401
internal.identifier.thesoz10081391
internal.identifier.thesoz10035505
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo618-638de
internal.identifier.classoz1080503
internal.identifier.journal1934
internal.identifier.document32
internal.identifier.ddc070
dc.identifier.doihttps://doi.org/10.1162/qss_a_00043de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
dc.subject.classhort10800de
ssoar.wgl.collectiontruede
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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