Abstract
Citation count is extensively used within research systems to measure research performance and relevance. However, high numbers of citations could result from many different factors. This paper proposes an adjusted citation count metric to help identify citations from researchers’ networks. Using data from the Web of Science core collection, this research suggests and illustrates an approach to compute the proportion of citation counts from within and out of author networks, defined as the set of their co-authors. The results reveal the trends and effects of author networks on citation counts. The paper explains how these findings could be used to assess research performance. Its utilisation will depend mainly on the objectives of the assessor and the stage of the researcher’s career. An algorithm is also proposed that could be used to automate the computation of the proposed metric. It could serve as a step towards refining and integrating this metric into existing bibliometric analysis packages built on the R software platform.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: COLLNET Journal of Scientometrics and Information Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
