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Investigating Bibliometrics tools for article screening in a Cochrane systematic review

dc.contributor.authorGracey, Catherine
dc.contributor.copyright-releaseNot Applicableen_US
dc.contributor.degreeMaster of Informationen_US
dc.contributor.departmentSchool of Information Managementen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinern/aen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.thesis-readerMelissa Rothfusen_US
dc.contributor.thesis-readerJill Haydenen_US
dc.contributor.thesis-supervisorPhilippe Mongeonen_US
dc.date.accessioned2024-04-15T18:32:08Z
dc.date.available2024-04-15T18:32:08Z
dc.date.defence2024-04-08
dc.date.issued2024-04-14
dc.description.abstractThis research applies bibliometric methods to a case study Cochrane review, to describe attributes of the groups of articles that were eligible for inclusion, included, and excluded for research integrity concerns. The variables of interest were the open access status of the articles, the type of funding received (if any), the article authors’ institution types, countries, and regions, the CiteScore of each journal that articles were published in, and the citation relationships between articles. These attributes were used to conduct a descriptive analysis of the makeup of each inclusion group, and predictive analysis, comprising of a logistic regression model that predicted inclusion/exclusion on the basis of research integrity concerns. This research proposes a model for using article, journal and author-based metrics to make predictions about the relevance of articles captured in the search, and quality of articles eligible for inclusion.en_US
dc.identifier.urihttp://hdl.handle.net/10222/83899
dc.language.isoenen_US
dc.subjectBibliometricsen_US
dc.subjectSystematic Reviewsen_US
dc.subjectCochraneen_US
dc.titleInvestigating Bibliometrics tools for article screening in a Cochrane systematic reviewen_US
dc.typeThesisen_US
dc.typeTexten_US

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