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.
Similar content being viewed by others
References
Dorta-González, P., & Dorta-González, M. I. (2011). Central indexes to the citation distribution: A complement to the h-index. Scientometrics, 88(3), 729–745.
Dorta-González, P., & Dorta-González, M. I. (2013a). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.
Dorta-González, P., & Dorta-González, M. I. (2013b). Hábitos de publicación y citación según campos científicos: Principales diferencias a partir de las revistas JCR. Revista Española de Documentación Científica, 36(4), en012.
Dorta-González, P., & Dorta-González, M. I. (2013c). Impact maturity times and citation time windows: The 2-year maximum journal impact factor. Journal of Informetrics, 7(3), 593–602.
Dorta-González, P., Dorta-González, M. I., Santos-Peñate, D. R., & Suárez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.
Egghe, L. (2013). Theoretical justification of the central area indices and the central interval indices. Scientometrics, 95(1), 25–34.
Egghe, L., & Rousseau, R. (2002). A general framework for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.
García-Pérez, M. A. (2013). Limited validity of equations to predict the future h index. Scientometrics, 96(3), 901–909.
Garfield, E. (1979). Is citation analysis a legitimate evaluation tool? Scientometrics, 1(4), 359–375.
Glänzel, W., Thijs, B., Schubert, A., & Debackere, K. (2009). Subfield-specific normalized relative indicators and a new generation of relational charts: Methodological foundations illustrated on the assessment of institutional research performance. Scientometrics, 78(1), 165–188.
González-Pereira, B., Guerrero-Bote, V. P., & Moya-Anegón, F. (2009). The SJR indicator: A new indicator of journals’ scientific prestige. Journal of Informetrics, 4(3), 379–391.
Leydesdorff, L. (2006). Can scientific journals be classified in terms of aggregated journal–journal citation relations using the journal citation reports? Journal of the American Society for Information Science and Technology, 57(5), 601–613.
Leydesdorff, L. (2012). Alternatives to the journal impact factor: I3 and the top-10 % (or top-25 %?) of the most-highly cited papers. Scientometrics, 92(2), 355–365.
Leydesdorff, L., & Bornmann, L. (2011). How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science. Journal of the American Society for Information Science and Technology, 62(2), 217–229.
Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5(1), 87–100.
Lundberg, J. (2007). Lifting the crown-citation z-score. Journal of Informetrics, 1(2), 145–154.
Mazloumian, A. (2012). Predicting scholars’ scientific impact. PLoS ONE, 7(11), e49246.
Moed, H. F. (2005). Citation analysis in research evaluation. New York: Springer.
Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4(3), 265–277.
Opthof, T., & Leydesdorff, L. (2010). Caveats for the journal and field normalizations in the CWTS (“Leiden”) evaluations of research performance. Journal of Informetrics, 4(3), 423–430.
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K., & Fortunato, S. (2013a). On the predictability of future impact in science. Scientific Reports, 3, 3052. doi:10.1038/srep03052.
Penner, O., Petersen, A. M., Pan, R. K., & Fortunato, S. (2013b). The case for caution in predicting scientists’ future impact. Physics Today, 66, 8–9.
Pudovkin, A. I., & Garfield, E. (2002). Algorithmic procedure for finding semantically related journals. Journal of the American Society for Information Science and Technology, 53(13), 1113–1119.
Rafols, I., & Leydesdorff, L. (2009). Content-based and algorithmic classifications of journals: Perspectives on the dynamics of scientific communication and indexer effects. Journal of the American Society for Information Science and Technology, 60(9), 1823–1835.
Rosvall, M., & Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4), 1118–1123.
Van Raan, A. F. J., Van Leeuwen, T. N., Visser, M. S., Van Eck, N. J., & Waltman, L. (2010). Rivals for the crown: Reply to Opthof and Leydesdorff. Journal of Informetrics, 4(3), 431–435.
Wagner, C., Roessner, J. D., Bobb, K., Klein, J., Boyack, K., Keyton, J., et al. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal of Informetrics, 5(1), 14–26.
Waltman, L., & Van Eck, N. J. (2013). Source normalized indicators of citation impact: An overview of different approaches and an empirical comparison. Scientometrics, 96(3), 699–716.
Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59(11), 1856–1860.
Conflict of interest
None.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Dorta-González, P., Dorta-González, M.I. & Suárez-Vega, R. An approach to the author citation potential: measures of scientific performance which are invariant across scientific fields. Scientometrics 102, 1467–1496 (2015). https://doi.org/10.1007/s11192-014-1459-4
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-014-1459-4