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An approach to the author citation potential: measures of scientific performance which are invariant across scientific fields
- Source :
- Scientometrics. 102:1467-1496
- Publication Year :
- 2014
- Publisher :
- Springer Science and Business Media LLC, 2014.
-
Abstract
- The citation potential is a measure of the probability of being cited. Obviously, it is different among fields of science, social science, and humanities because of systematic differences in publication and citation behaviour across disciplines. In the past, the citation potential was studied at journal level considering the average number of references in established groups of journals (for example, the crown indicator is based on the journal subject categories in the Web of Science database). In this paper, some characterizations of the author's scientific research through three different research dimensions are proposed: production (journal papers), impact (journal citations), and reference (bibliographical sources). Then, we propose different measures of the citation potential for authors based on a proportion of these dimensions. An empirical application, in a set of 120 randomly selected highly productive authors from the CSIC Research Centre (Spain) in four subject areas, shows that the ratio between production and impact dimensions is a normalized measure of the citation potential at the level of individual authors. Moreover, this ratio reduces the between-group variance in relation to the within-group variance in a higher proportion than the rest of the indicators analysed. Furthermore, it is consistent with the type of journal impact indicator used. A possible application of this result is in the selection and promotion process within interdisciplinary institutions, since it allows comparisons of authors based on their particular scientific research.<br />Comment: 31 pages, 4 figures and 7 tables. arXiv admin note: text overlap with arXiv:1402.6317, arXiv:1304.5101; and with arXiv:1003.2167 by other authors
- Subjects :
- FOS: Computer and information sciences
Impact indicator
Computer science
General Social Sciences
Author citation
Computer Science - Digital Libraries
Library and Information Sciences
Data science
Computer Science Applications
Research centre
Citation analysis
Econometrics
Subject areas
Digital Libraries (cs.DL)
Invariant (mathematics)
Citation
Subjects
Details
- ISSN :
- 15882861 and 01389130
- Volume :
- 102
- Database :
- OpenAIRE
- Journal :
- Scientometrics
- Accession number :
- edsair.doi.dedup.....41245cde51c851fc2048960757c49dbf
- Full Text :
- https://doi.org/10.1007/s11192-014-1459-4