Advertisement

Scientometrics

, Volume 112, Issue 1, pp 403–412 | Cite as

An empirical investigation of the associations among usage, scientific collaboration and citation impact

  • Pei-Shan ChiEmail author
  • Wolfgang Glänzel
Article

Abstract

In this study usage counts and times cited from Web of Science Core Collection (WoS) were collected for articles published in 2013 with Belgian, Israeli and Iranian addresses. We investigated the relations among three indicators related to citation impact, usage counts and co-authorship, respectively. In addition, we applied the method of Characteristic Scores and Scales (CSS) to analyse the distributions of citations and usage counts to further test the relation between the usage and citation impact. The results show that citations and usage counts in WoS correlate significantly, especially in the social sciences. However, higher numbers of co-authors are not associated with higher usage counts or citations. Furthermore, the stability of CSS-class distributions substantiates the applicability of CSS in characterising both usage and citation distributions. Distinctly different patterns in citations and usage are observed, but the similarities within citations and usage in these fields are somewhat unexpected.

Keywords

Citations WoS usage Scientific collaboration Characteristic Scores and Scales 

Notes

Acknowledgements

This paper is an extended version of a previous work presented at the 21st STI Conference in Valencia, Spain (Chi and Glänzel 2016).

References

  1. Bollen, J., van de Sompel, H., Hagberg, A., & Chute, R. (2009). A principal component analysis of 39 scientific impact measures. PLoS ONE, 4(6), e6022.CrossRefGoogle Scholar
  2. Bornmann, L. (2015). Alternative metrics in scientometrics: A meta-analysis of research into three altmetrics. Scientometrics, 103(3), 1123–1144.CrossRefGoogle Scholar
  3. Brody, T., Harnad, S., & Carr, L. (2006). Earlier web usage statistics as predictors of later citation impact. Journal of the American Society for Information Science and Technology, 57(8), 1060–1072.CrossRefGoogle Scholar
  4. Chi, P.S. & Glänzel, W. (2016). Do usage and scientific collaboration associate with citation impact? In I. Ràfols, J. Molas-Gallart, E. Castro-Martínez & R. Woolley (Eds.), Proceedings of the 21st international conference on science and technology indicators, València (pp. 1223–1228).Google Scholar
  5. Cronin, B., Shaw, D., & La Barre, K. (2004). Visible, less visible, and invisible work: Patterns of collaboration in 20th century chemistry. Journal of the American Society for Information Science and Technology, 55(2), 160–168.CrossRefGoogle Scholar
  6. Glänzel, W. & Heeffer, S. (2014). Cross-national preferences and similarities in downloads and citations of scientific articles: A pilot study. In E. Noyons (Ed.), Proceedings of the STI Conference 2014, Leiden (pp. 207–215).Google Scholar
  7. Glänzel, W., & Schubert, A. (1988). Characteristic scores and scales in assessing citation impact. Journal of Information Science, 14(2), 123–127.CrossRefGoogle Scholar
  8. Glänzel, W., & Schubert, A. (2003). A new classification scheme of science fields and subfields designed for scientometric evaluation purposes. Scientometrics, 56(3), 357–367.CrossRefGoogle Scholar
  9. Glänzel, W., & Thijs, B. (2004). Does co-authorship inflate the share of self-citations? Scientometrics, 61(3), 395–404.CrossRefGoogle Scholar
  10. Glänzel, W., Thijs, B., & Chi, P. S. (2016). The challenges to expand bibliometric studies from periodical literature to monographic literature with a new data source: The book citation index. Scientometrics, 109(3), 2165–2179.CrossRefGoogle Scholar
  11. Glänzel, W., Thijs, B., & Debackere, K. (2014). The application of citation-based performance classes to the disciplinary and multidisciplinary assessment in national comparison and institutional research assessment. Scientometrics, 101(2), 939–952.CrossRefGoogle Scholar
  12. Grossman, J. W. (2002). The evolution of the mathematical research collaboration graph. Congressus Numeratium, 158, 202–212.MathSciNetzbMATHGoogle Scholar
  13. Hammarfelt, B. (2014). Using altmetrics for assessing research impact in the humanities. Scientometrics, 101(2), 1419–1430.CrossRefGoogle Scholar
  14. Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213–238.CrossRefGoogle Scholar
  15. Persson, O., Glänzel, W., & Danell, R. (2004). Inflationary bibliometric values: The role of scientific collaboration and the need for relative indicators in evaluative studies. Scientometrics, 60(3), 421–432.CrossRefGoogle Scholar
  16. Peters, H. P. F., & van Raan, A. F. J. (1994). On determinants of citation scores: A case study in chemical engineering. Journal of the American Society for Information Science and Technology, 45(1), 39–49.CrossRefGoogle Scholar
  17. Sonnenwald, D. H. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41(1), 643–681.CrossRefGoogle Scholar
  18. Wang, X., Fang, Z., & Sun, X. (2016). Usage patterns of scholarly articles on Web of Science: A study on Web of Science usage count. Scientometrics, 109(2), 917–926.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2017

Authors and Affiliations

  1. 1.ECOOM and Department of MSIKU LeuvenLouvainBelgium
  2. 2.Department of Science Policy and ScientometricsLibrary of the Hungarian Academy of SciencesBudapestHungary

Personalised recommendations