2.50
Hdl Handle:
http://hdl.handle.net/2436/620327
Title:
Three practical field normalised alternative indicator formulae for research evaluation
Authors:
Thelwall, Mike ( 0000-0001-6065-205X )
Abstract:
Although altmetrics and other web-based alternative indicators are now commonplace in publishers’ websites, they can be difficult for research evaluators to use because of the time or expense of the data, the need to benchmark in order to assess their values, the high proportion of zeros in some alternative indicators, and the time taken to calculate multiple complex indicators. These problems are addressed here by (a) a field normalisation formula, the Mean Normalised Log-transformed Citation Score (MNLCS) that allows simple confidence limits to be calculated and is similar to a proposal of Lundberg, (b) field normalisation formulae for the proportion of cited articles in a set, the Equalised Mean-based Normalised Proportion Cited (EMNPC) and the Mean-based Normalised Proportion Cited (MNPC), to deal with mostly uncited data sets, (c) a sampling strategy to minimise data collection costs, and (d) free unified software to gather the raw data, implement the sampling strategy, and calculate the indicator formulae and confidence limits. The approach is demonstrated (but not fully tested) by comparing the Scopus citations, Mendeley readers and Wikipedia mentions of research funded by Wellcome, NIH, and MRC in three large fields for 2013–2016. Within the results, statistically significant differences in both citation counts and Mendeley reader counts were found even for sets of articles that were less than six months old. Mendeley reader counts were more precise than Scopus citations for the most recent articles and all three funders could be demonstrated to have an impact in Wikipedia that was significantly above the world average.
Publisher:
Elsevier
Journal:
Journal of Informetrics
Issue Date:
Feb-2017
URI:
http://hdl.handle.net/2436/620327
Additional Links:
http://www.sciencedirect.com/science/article/pii/S175115771630205X
Type:
Article
Language:
en
ISSN:
1751-1577
Appears in Collections:
Statistical Cybermetrics Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorThelwall, Mikeen
dc.date.accessioned2017-01-05T12:14:05Z-
dc.date.available2017-01-05T12:14:05Z-
dc.date.issued2017-02-
dc.identifier.issn1751-1577en
dc.identifier.urihttp://hdl.handle.net/2436/620327-
dc.description.abstractAlthough altmetrics and other web-based alternative indicators are now commonplace in publishers’ websites, they can be difficult for research evaluators to use because of the time or expense of the data, the need to benchmark in order to assess their values, the high proportion of zeros in some alternative indicators, and the time taken to calculate multiple complex indicators. These problems are addressed here by (a) a field normalisation formula, the Mean Normalised Log-transformed Citation Score (MNLCS) that allows simple confidence limits to be calculated and is similar to a proposal of Lundberg, (b) field normalisation formulae for the proportion of cited articles in a set, the Equalised Mean-based Normalised Proportion Cited (EMNPC) and the Mean-based Normalised Proportion Cited (MNPC), to deal with mostly uncited data sets, (c) a sampling strategy to minimise data collection costs, and (d) free unified software to gather the raw data, implement the sampling strategy, and calculate the indicator formulae and confidence limits. The approach is demonstrated (but not fully tested) by comparing the Scopus citations, Mendeley readers and Wikipedia mentions of research funded by Wellcome, NIH, and MRC in three large fields for 2013–2016. Within the results, statistically significant differences in both citation counts and Mendeley reader counts were found even for sets of articles that were less than six months old. Mendeley reader counts were more precise than Scopus citations for the most recent articles and all three funders could be demonstrated to have an impact in Wikipedia that was significantly above the world average.en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S175115771630205Xen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectScientometricsen
dc.subjectAltmetricsen
dc.subjectWebometricsen
dc.subjectWeb indictorsen
dc.titleThree practical field normalised alternative indicator formulae for research evaluationen
dc.typeArticleen
dc.identifier.journalJournal of Informetricsen
dc.date.accepted2016-12-
rioxxterms.funderInternalen
rioxxterms.identifier.projectUoW050117MTen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/CC BY-NC-ND 4.0en
rioxxterms.licenseref.startdate2018-02-01en
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