Skip to main content
Log in

Interpreting correlations between citation counts and other indicators

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Altmetrics or other indicators for the impact of academic outputs are often correlated with citation counts in order to help assess their value. Nevertheless, there are no guidelines about how to assess the strengths of the correlations found. This is a problem because the correlation strength affects the conclusions that should be drawn. In response, this article uses experimental simulations to assess the correlation strengths to be expected under various different conditions. The results show that the correlation strength reflects not only the underlying degree of association but also the average magnitude of the numbers involved. Overall, the results suggest that due to the number of assumptions that must be made, in practice it will rarely be possible to make a realistic interpretation of the strength of a correlation coefficient.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics, 8(4), 985–996.

    Article  Google Scholar 

  • Ajiferuke, I., & Famoye, F. (2015). Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models. Journal of Informetrics, 9(3), 499–513.

    Article  Google Scholar 

  • Bosquet, C., & Combes, P. P. (2013). Are academics who publish more also more cited? Individual determinants of publication and citation records. Scientometrics, 97(3), 831–857.

    Article  Google Scholar 

  • Brzezinski, M. (2015). Power laws in citation distributions: Evidence from Scopus. Scientometrics, 103(1), 213–228.

    Article  Google Scholar 

  • Chakraborty, T., Tammana, V., Ganguly, N., & Mukherjee, A. (2015). Understanding and modeling diverse scientific careers of researchers. Journal of Informetrics, 9(1), 69–78.

    Article  Google Scholar 

  • Clauset, A., Shalizi, C. R., & Newman, M. E. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703.

    Article  MathSciNet  MATH  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Abingdon: Lawrence Erlbaum Associates.

    MATH  Google Scholar 

  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. doi:10.1037/0033-2909.112.1.155.

    Article  Google Scholar 

  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.

    Article  Google Scholar 

  • Didegah, F., & Thelwall, M. (2013). Which factors help authors produce the highest impact research? Collaboration, journal and document properties. Journal of Informetrics, 7(4), 861–873.

    Article  Google Scholar 

  • Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Else, H. (2015). Research funding formula tweaked after REF 2014 results. https://www.timeshighereducation.com/news/research-funding-formula-tweaked-after-ref-2014-results/2018685.article.

  • Eom, Y. H., & Fortunato, S. (2011). Characterizing and modeling citation dynamics. PLoS ONE, 6(9), e24926.

    Article  Google Scholar 

  • Ettori, S. (2015). The physics inside the scaling relations for X-ray galaxy clusters: Gas clumpiness, gas mass fraction and slope of the pressure profile. Monthly Notices of the Royal Astronomical Society, 446(3), 2629–2639.

    Article  Google Scholar 

  • Finardi, U. (2013). Correlation between journal impact factor and citation performance: An experimental study. Journal of Informetrics, 7(2), 357–370.

    Article  Google Scholar 

  • Franceschet, M., & Costantini, A. (2011). The first Italian research assessment exercise: A bibliometric perspective. Journal of Informetrics, 5(2), 275–291.

    Article  Google Scholar 

  • Garanina, O. S., & Romanovsky, M. Y. (2015). Citation distribution of individual scientist: Approximations of stretch exponential distribution with power law tails. In A. A. Salah, Y. Tonta, A. A. Akdag Salah, C. Sugimoto, & U. Al (Eds.), Proceedings of ISSI 2015 (pp. 272–277). Turkey: Bogaziçi University Printhouse.

    Google Scholar 

  • Gillespie, C.S. (2015). Fitting heavy tailed distributions: the poweRlaw package. Journal of Statistical Software, 64(2), 1–16. http://www.jstatsoft.org/v64/i02/paper.

  • Hartley, J., & Sydes, M. (1997). Are structured abstracts easier to read than traditional ones? Journal of Research in Reading, 20(2), 122–136.

    Article  Google Scholar 

  • HEFCE. (2015). The metric tide: Correlation analysis of REF2014 scores and metrics. Supplementary Report II to the Independent review of the role of metrics in research assessment and management. Bristol: Hefce. http://www.hefce.ac.uk/pubs/rereports/Year/2015/metrictide/Title,104463,en.html.

  • Hemphill, J. F. (2003). Interpreting the magnitudes of correlation coefficients. American Psychologist, 58(1), 78–79.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Hyland, K. (1999). Academic attribution: Citation and the construction of disciplinary knowledge. Applied Linguistics, 20(3), 341–367.

    Article  MathSciNet  Google Scholar 

  • Kostoff, R. (2007). The difference between highly and poorly cited medical articles in the journal Lancet. Scientometrics, 72, 513–520.

    Article  Google Scholar 

  • Kousha, K., & Thelwall, M. (2015). Web indicators for research evaluation, part 3: Books and non-standard outputs. El Profesional de la Información, 24(6), 724–736. doi:10.3145/epi.2015.nov.04.

    Article  Google Scholar 

  • Larivière, V., & Gingras, Y. (2010). On the relationship between interdisciplinarity and scientific impact. Journal of the American Society for Information Science and Technology, 61, 126–131.

    Article  Google Scholar 

  • Limpert, E., Stahel, W. A., & Abbt, M. (2001). Lognormal distribution across sciences: Key and clues. BioScience, 51(5), 341–351.

    Article  Google Scholar 

  • Lipsey, M.W., Puzio, K., Yun, C., Hebert, M.A., Steinka-Fry, K., Cole, M.W., et al. (2012). Translating the statistical representation of the effects of education interventions into more readily interpretable forms. Washington, DC: US Dept of Education, National Center for Special Education Research, Institute of Education Sciences, NCSER 2013-3000.

  • Liu, G., Qi, X. L., Robert, N., Dick, A. J., & Wright, G. A. (2012). Ultrasound-guided identification of cardiac imaging windows. Medical Physics, 39(6), 3009–3018.

    Article  Google Scholar 

  • Low, W. J., Thelwall, M., & Wilson, P. (2015). Stopped sum models for citation data. In A. A. Salah, Y. Tonta, A. A. AkdagSalah, C. Sugimoto, & U. Al (Eds.), Proceedings of ISSI 2015 Istanbul: 15th international society of scientometrics and informetrics conference (pp. 184–194). Istanbul: Bogaziçi University Printhouse.

    Google Scholar 

  • Mohammadi, E., & Thelwall, M. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the American Society for Information Science and Technology, 65(8), 1627–1638.

    Article  Google Scholar 

  • Onodera, N., & Yoshikane, F. (2015). Factors affecting citation rates of research articles. Journal of the Association for Information Science and Technology, 66(4), 739–764.

    Article  Google Scholar 

  • Oppenheim, C. (2000). Do patent citations count? In B. Cronin & H. B. Atkins (Eds.), The web of knowledge: A festschrift in honor of Eugene Garfield (pp. 405–432). Metford: Information Today Inc. ASIS Monograph Series.

    Google Scholar 

  • Pennock, D. M., Flake, G. W., Lawrence, S., Glover, E. J., & Giles, C. L. (2002). Winners don’t take all: Characterizing the competition for links on the web. Proceedings of the National Academy of Sciences, 99(8), 5207–5211.

    Article  MATH  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Radicchi, F., Fortunato, S., & Castellano, C. (2008). Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences, 105(45), 17268–17272.

    Article  Google Scholar 

  • Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B-Condensed Matter and Complex Systems, 4(2), 131–134.

    Article  Google Scholar 

  • Sud, P., & Thelwall, M. (2014). Evaluating altmetrics. Scientometrics, 98(2), 1131–1143. doi:10.1007/s11192-013-1117-2.

    Article  Google Scholar 

  • Thelwall, M. (2006). Interpreting social science link analysis research: A theoretical framework. Journal of the American Society for Information Science and Technology, 57(1), 60–68.

    Article  Google Scholar 

  • Thelwall, M. (2016). The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression. Journal of Informetrics, 10(2), 336–346. doi:10.1016/j.joi.2015.12.007.

    Article  Google Scholar 

  • Thelwall, M., & Fairclough, R. (2015). The influence of time and discipline on the magnitude of correlations between citation counts and quality scores. Journal of Informetrics, 9(3), 529–541. doi:10.1016/j.joi.2015.05.006.

    Article  Google Scholar 

  • Thelwall, M., & Kousha, K. (2015a). Web indicators for research evaluation, Part 1: Citations and links to academic articles from the web. El Profesional de la Información, 24(5), 587–606. doi:10.3145/epi.2015.sep.08.

    Article  Google Scholar 

  • Thelwall, M., & Kousha, K. (2015b). Web indicators for research evaluation, Part 2: Social media metrics. El Profesional de la Información, 24(5), 607–620. doi:10.3145/epi.2015.sep.09.

    Article  Google Scholar 

  • Thelwall, M., & Wilson, P. (2014). Distributions for cited articles from individual subjects and years. Journal of Informetrics, 8(4), 824–839.

    Article  Google Scholar 

  • Thelwall, M., & Wilson, P. (in press). Mendeley readership altmetrics for medical articles: An analysis of 45 fields. Journal of the Association for Information Science and Technology. doi:10.1002/asi.23501.

  • van Raan, A. (1998). The influence of international collaboration on the impact of research results: Some simple mathematical considerations concerning the role of self-citations. Scientometrics, 42(3), 423–428.

    Article  Google Scholar 

  • Wainer, J., & Vieira, P. (2013). Correlations between bibliometrics and peer evaluation for all disciplines: the evaluation of Brazilian scientists. Scientometrics, 96(2), 395–410.

    Article  Google Scholar 

  • Wilsdon, J., Allen, L., Belfiore, E., Campbell, P., Curry, S., Hill, S., et al. (2015). The metric tide: Report of the independent review of the role of metrics in research assessment and management. http://www.hefce.ac.uk/pubs/rereports/Year/2015/metrictide/Title,104463,en.html.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mike Thelwall.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thelwall, M. Interpreting correlations between citation counts and other indicators. Scientometrics 108, 337–347 (2016). https://doi.org/10.1007/s11192-016-1973-7

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-016-1973-7

Keywords

Navigation