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dc.contributor.authorShahmandi, Marzieh
dc.contributor.authorWilson, Paul
dc.contributor.authorThelwall, Michael
dc.date.accessioned2020-08-13T08:47:03Z
dc.date.available2020-08-13T08:47:03Z
dc.date.issued2020-08-17
dc.identifier.citationShahmandi, M., Wilson, P. and Thelwall, M. (2020) A new algorithm for zero-modified models applied to citation counts. Scientometrics, 125, pp. 993–1010.en
dc.identifier.issn0138-9130en
dc.identifier.doi10.1007/s11192-020-03654-8
dc.identifier.urihttp://hdl.handle.net/2436/623482
dc.descriptionThis is an accepted manuscript of an article published by Springer Nature in Scientometrics on 17/08/2020, available online: https://doi.org/10.1007/s11192-020-03654-8. The accepted version of the publication may differ from the final published version.en
dc.description.abstractFinding statistical models for citation count data is important for those seeking to understand the citing process or when using regression to identify factors that associate with citation rates. As sets of citation counts often include more or less zeros (uncited articles) than would be expected under the base distribution, it is essential to deal appropriately with them. This article proposes a new algorithm to fit zero-modified versions of discretised lognormal, hooked power-law and Weibull models to citation count data from 23 different Scopus categories from 2012. The new algorithm allows the standard errors of all parameter estimates to be calculated, and hence also confidence intervals and p-values. This algorithm can also estimate negative zero-modification parameters corresponding to zero-deflation (fewer uncited articles than expected). The results find no universal best model for the 23 categories. A given dataset may be zero-inflated relative to one model, but zero-deflated relative to another. We suggest circumstances in which one of the models under consideration may be the best fitting model.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherSpringer Natureen
dc.relation.urlhttps://link.springer.com/article/10.1007/s11192-020-03654-8en
dc.subjectzero inflationen
dc.subjectzero modificationen
dc.subjectzero deflationen
dc.subjectcitation count modelsen
dc.subjectcitation analysisen
dc.titleA new algorithm for zero-modified models applied to citation countsen
dc.typeJournal articleen
dc.identifier.journalScientometricsen
dc.date.updated2020-07-30T06:13:05Z
dc.date.accepted2020-07-01
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW13082020MTen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-12-31en
dc.source.volume125
dc.source.beginpage993
dc.source.endpage1010
refterms.dateFCD2020-08-13T08:43:00Z
refterms.versionFCDAM


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