2.50
Hdl Handle:
http://hdl.handle.net/2436/614827
Title:
Interpreting correlations between citation counts and other indicators
Authors:
Thelwall, Mike
Abstract:
Altmetrics or other indicators for the impact of academic outputs are often correlated with citation counts in order to help assess their value. Nevertheless, there are no guidelines about how to assess the strengths of the correlations found. This is a problem because this value affects the conclusions that should be drawn. In response, this article uses experimental simulations to assess the correlation strengths to be expected under various different conditions. The results show that the correlation strength reflects not only the underlying degree of association but also the average magnitude of the numbers involved. Overall, the results suggest that due to the number of assumptions that must be made in practice it will rarely be possible to make a realistic interpretation of the strength of a correlation coefficient.
Citation:
Interpreting correlations between citation counts and other indicators 2016 Scientometrics
Publisher:
Springer
Journal:
Scientometrics
Issue Date:
9-May-2016
URI:
http://hdl.handle.net/2436/614827
DOI:
10.1007/s11192-016-1973-7
Additional Links:
http://link.springer.com/10.1007/s11192-016-1973-7
Type:
Article
Language:
en
ISSN:
0138-9130
Appears in Collections:
Statistical Cybermetrics Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorThelwall, Mikeen
dc.date.accessioned2016-06-27T13:51:18Z-
dc.date.available2016-06-27T13:51:18Z-
dc.date.issued2016-05-09-
dc.identifier.citationInterpreting correlations between citation counts and other indicators 2016 Scientometricsen
dc.identifier.issn0138-9130en
dc.identifier.doi10.1007/s11192-016-1973-7-
dc.identifier.urihttp://hdl.handle.net/2436/614827-
dc.description.abstractAltmetrics or other indicators for the impact of academic outputs are often correlated with citation counts in order to help assess their value. Nevertheless, there are no guidelines about how to assess the strengths of the correlations found. This is a problem because this value affects the conclusions that should be drawn. In response, this article uses experimental simulations to assess the correlation strengths to be expected under various different conditions. The results show that the correlation strength reflects not only the underlying degree of association but also the average magnitude of the numbers involved. Overall, the results suggest that due to the number of assumptions that must be made in practice it will rarely be possible to make a realistic interpretation of the strength of a correlation coefficient.en
dc.language.isoenen
dc.publisherSpringeren
dc.relation.urlhttp://link.springer.com/10.1007/s11192-016-1973-7en
dc.rightsArchived with thanks to Scientometricsen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCitation analysisen
dc.subjectcorrelationsen
dc.subjectAltmetricsen
dc.subjectIndicatorsen
dc.subjectDiscretised lognormalen
dc.subjectSimulationen
dc.titleInterpreting correlations between citation counts and other indicatorsen
dc.typeArticleen
dc.identifier.journalScientometricsen
dc.date.accepted2016-05-03-
rioxxterms.funderInternalen
rioxxterms.identifier.projectUnfundeden
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/CC BY-NC-ND 4.0en
rioxxterms.licenseref.startdate2017-05-08en
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