Author:

Keywords:

Science & Technology, Technology, Computer Science, Interdisciplinary Applications, Information Science & Library Science, Computer Science, Characteristic scores and scales, Citation distributions, Performance classes, Crossnational, Comparison, Institutional assessment, CHARACTERISTIC SCORES, DISTRIBUTIONS, SCALES, IMPACT, TAIL, 0807 Library and Information Studies, 1605 Policy and Administration, Science Studies, 4610 Library and information studies, 4901 Applied mathematics

Abstract:

© 2014, Akadémiai Kiadó, Budapest, Hungary. The analysis of the high end of citation distributions represented by its tail provides important supplementary information on the citation profile of the unit under study. In a previous study by Glänzel (Scientometrics 97:13–23, 2013a), a parameter-free solution providing four performance classes has been proposed. Unlike in methods based on pre-set percentiles, this method is not sensitive to ties and ensures needless integration of measures of outstanding and even extreme performance into the standard tools of scientometric performance assessment. The applicability of the proposed method is demonstrated for both subject analysis and the combination of different subjects at the macro and meso level.