Improved author profiling through the use of citation classes

Bart Thijs (), Koenraad Debackere () and Wolfgang Glänzel ()
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Bart Thijs: KU Leuven
Koenraad Debackere: KU Leuven
Wolfgang Glänzel: KU Leuven

Scientometrics, 2017, vol. 111, issue 2, No 12, 829-839

Abstract: Abstract The method of Characteristic Scores and Scales (CSS), previously developed for application at the macro- and meso-level, has been applied to individual author statistics. In particular, two datasets have been used. Firstly, authors with Thomson Reuters Researcher-ID, independently of the field where authors are publishing and, secondly, authors who are active in the field of scientometrics, independently whether they are registered authors or not. The objective is to find a parameter-free solution for citation-impact assessment at this level of aggregation that is insensitive to possible outliers. As in the case of any statistics, the only limitation is the lower bound, which has been set to 10 for the present analysis. The results demonstrate the usefulness of the CSS method at this level while also pointing to some remarkable statistical properties.

Keywords: Evaluatieve bibliometrics; Citation classes; Characteristic scores and scales (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11192-017-2282-5

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