Can alternative indicators overcome language biases in citation counts? A comparison of Spanish and UK research
Amalia Mas-Bleda () and
Mike Thelwall
Additional contact information
Amalia Mas-Bleda: University of Wolverhampton
Mike Thelwall: University of Wolverhampton
Scientometrics, 2016, vol. 109, issue 3, No 30, 2007-2030
Abstract:
Abstract This study compares Spanish and UK research in eight subject fields using a range of bibliometric and social media indicators. For each field, lists of Spanish and UK journal articles published in the year 2012 and their citation counts were extracted from Scopus. The software Webometric Analyst was then used to extract a range of altmetrics for these articles, including patent citations, online presentation mentions, online course syllabus mentions, Wikipedia mentions and Mendeley reader counts and Altmetric.com was used to extract Twitter mentions. Results show that Mendeley is the altmetric source with the highest coverage, with 80 % of sampled articles having one or more Mendeley readers, followed by Twitter (34 %). The coverage of the remaining sources was lower than 3 %. All of the indicators checked either have too little data or increase the overall difference between Spain and the UK and so none can be suggested as alternatives to reduce the bias against Spain in traditional citation indexes.
Keywords: Altmetrics; Social media metrics; Alternative indicators; Country comparison; Language bias; Research production (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-016-2118-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2118-8
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-016-2118-8
Access Statistics for this article
Scientometrics is currently edited by Wolfgang Glänzel
More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().