Scientometrics

, Volume 84, Issue 3, pp 749–762 | Cite as

The discipline dependence of citation statistics

Article

Abstract

This study compares the citations characteristics of researchers in engineering disciplines with other major scientific disciplines, and investigates variations in citing patterns within subdisciplines in the field of engineering. Utilizing citations statistics including Hirsch’s (Proc Natl Acad Sci USA 102(46):16569–16572, 2005) h-index value, we find that significant differences in citing characteristics exist between engineering disciplines and other scientific fields. Our findings also reveal statistical differences in citing characteristics between subdisciplines found within the same engineering discipline.

Keywords

Citations H-index Discipline Field Statistics 

Notes

Acknowledgements

We would like to thank the National Sciences and Research Council of Canada for their financial support of our study. The technical assistance of Monika Pakstas is gratefully acknowledged.

References

  1. Batista, P. D., Campiteli, M. G., Kinouchi, O., & Martinez, A. S. (2006). Is it possible to compare researchers with different scientific interests? Scientometrics, 68(1), 179–189.CrossRefGoogle Scholar
  2. Bollen, J., & Van de Sompel, H. (2008). Usage impact factor: the effects of sample characteristics on usage-based impact metrics. Journal of the American Society for Information Science and Technology, 59(1), 136–149.CrossRefGoogle Scholar
  3. Bornmann, L., & Daniel, H.-D. (2007). What do we know about the h-index? Journal of the American Society for Information Science and Technology, 58(9), 1381–1385.CrossRefGoogle Scholar
  4. Costas, R., & Bordons, M. (2007). The h-index: advantages, limitations and its relation with other bibliometric indicators at the micro level. Journal of Informetrics, 1(2), 193–203.CrossRefGoogle Scholar
  5. Glänzel, W., Debackere, K., Thijs, B., & Schubert, A. (2005). A concise review on the role of author self-citations in information science, bibliometrics and science policy. Scientometrics, 67(2), 263–277.CrossRefGoogle Scholar
  6. Guerrero-Bote, V. P., Zapico-Alonso, F., Espinosa-Calvo, M. E., Gómez-Crisóstomo, R., & De Moya-Anegón, F. (2007). Import-export of knowledge between scientific subject categories: The iceberg hypothesis. Scientometrics, 71(3), 423–441.CrossRefGoogle Scholar
  7. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572.CrossRefGoogle Scholar
  8. Iglesias, J. E., & Pecharromán, C. (2007). Scaling the h-index for different scientific ISI fields. Scientometrics, 73(3), 303–320.CrossRefGoogle Scholar
  9. Keselman, H. J., Othman, A. R., Wilcox, R. R., & Fradette, K. (2004). The new and improved two-sample t test. Psychological Science, 15(1), 47–51.CrossRefGoogle Scholar
  10. Meho, L. I., & Yang, K. (2007). Impact of data sources on citation counts and rankings of LIS faculty: Web of science versus Scopus and Google Scholar. Journal of the American Society for Information Science and Technology, 58(13), 2105–2125.CrossRefGoogle Scholar
  11. Podlubny, I. (2005). Comparison of scientific impact expressed by the number of citations in different fields of science. Scientometrics, 64(1), 95–99.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2010

Authors and Affiliations

  1. 1.Department of GeographyThe University of British ColumbiaVancouverCanada
  2. 2.Department of Mechanical EngineeringThe University of British ColumbiaVancouverCanada

Personalised recommendations