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Are Mendeley reader counts useful impact indicators in all fields?

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Abstract

Reader counts from the social reference sharing site Mendeley are known to be valuable for early research evaluation. They have strong correlations with citation counts for journal articles but appear about a year before them. There are disciplinary differences in the value of Mendeley reader counts but systematic evidence is needed at the level of narrow fields to reveal its extent. In response, this article compares Mendeley reader counts with Scopus citation counts for journal articles from 2012 in 325 narrow Scopus fields. Despite strong positive correlations in most fields, averaging 0.671, the correlations in some fields are as weak as 0.255. Technical reasons explain most weaker correlations, suggesting that the underlying relationship is almost always strong. The exceptions are caused by unusually high educational or professional use or topics of interest within countries that avoid Mendeley. The findings suggest that if care is taken then Mendeley reader counts can be used for early citation impact evidence in almost all fields and for related impact in some of the remainder. As an additional application of the results, cross-checking with Mendeley data can be used to identify indexing anomalies in citation databases.

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Notes

  1. https://blog.mendeley.com/2011/10/25/howto-use-mendeley-to-create-citations-using-latex-and-bibtex/.

References

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2011). Assessing the varying level of impact measurement accuracy as a function of the citation window length. Journal of Informetrics, 5(4), 659–667.

    Article  Google Scholar 

  • Aksnes, D. W., & Taxt, R. E. (2004). Peer reviews and bibliometric indicators: A comparative study at a Norwegian university. Research Evaluation, 13(1), 33–41.

    Article  Google Scholar 

  • Bar-Ilan, J. (2014). Astrophysics publications on arXiv, Scopus and Mendeley: A case study. Scientometrics, 100(1), 217–225.

    Article  Google Scholar 

  • Campanario, J. M. (2011). Empirical study of journal impact factors obtained using the classical two-year citation window versus a five-year citation window. Scientometrics, 87(1), 189–204.

    Article  Google Scholar 

  • Franceschini, F., Maisano, D., & Mastrogiacomo, L. (2015). Errors in DOI indexing by bibliometric databases. Scientometrics, 102(3), 2181–2186.

    Article  Google Scholar 

  • Gorraiz, J., Melero-Fuentes, D., Gumpenberger, C., & Valderrama-Zurián, J. C. (2016). Availability of digital object identifiers (DOIs) in Web of Science and Scopus. Journal of Informetrics, 10(1), 98–109.

    Article  Google Scholar 

  • Halevi, G., Moed, H., & Bar-Ilan, J. (2017). Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the literature. Journal of Informetrics, 11(3), 823–834.

    Article  Google Scholar 

  • Harzing, A. W., & Alakangas, S. (2017). Microsoft academic is one year old: The phoenix is ready to leave the nest. Scientometrics, 112(3), 1887–1894.

    Article  Google Scholar 

  • Haustein, S., Bowman, T. D., & Costas, R. (2015). When is an article actually published? An analysis of online availability, publication, and indexation dates. In: 15th International conference on scientometrics and informetrics (ISSI2015) (pp. 1170–1179).

  • Haustein, S., Larivière, V., Thelwall, M., Amyot, D., & Peters, I. (2014). Tweets vs. Mendeley readers: How do these two social media metrics differ? IT-Information Technology, 56(5), 207–215.

    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). http://www.hefce.ac.uk/pubs/rereports/Year/2015/metrictide/Title,104463,en.html.

  • Hug, S. E., Ochsner, M., & Brändle, M. P. (2017). Citation analysis with Microsoft Academic. Scientometrics, 111(1), 371–378.

    Article  Google Scholar 

  • Maflahi, N., & Thelwall, M. (2016). When are readership counts as useful as citation counts? Scopus versus Mendeley for LIS journals. Journal of the Association for Information Science and Technology, 67(1), 191–199.

    Article  Google Scholar 

  • Maflahi, N, & Thelwall, M. (2017). How quickly do publications get read? The evolution of Mendeley reader counts for new articles. Journal of the Association for Information Science and Technology. doi:10.1002/asi.23909.

  • Merton, R. K. (1968). The Matthew effect in science. Science, 159(3810), 56–63.

    Article  Google Scholar 

  • Merton, R. K. (1973). The sociology of science: Theoretical and empirical investigations. Chicago: University of Chicago press.

    Google Scholar 

  • Moed, F., & Visser, M. S. (2008). Appraisal of citation data sources. http://www.hefce.ac.uk/media/hefce/content/pubs/indirreports/2008/missing/Appraisal%20of%20Citation%20Data%20Sources.pdf.

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

    Article  Google Scholar 

  • Mohammadi, E., Thelwall, M., Haustein, S., & Larivière, V. (2015). Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the Association for Information Science and Technology, 66(9), 1832–1846.

    Article  Google Scholar 

  • Mohammadi, E., Thelwall, M., & Kousha, K. (2016). Can Mendeley bookmarks reflect readership? A survey of user motivations. Journal of the Association for Information Science and Technology., 67(5), 1198–1209. doi:10.1002/asi.23477.

    Article  Google Scholar 

  • Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228.

    Article  Google Scholar 

  • Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2011). Altmetrics: A manifesto. http://altmetrics.org/manifesto.

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

    Article  Google Scholar 

  • Thelwall, M. (2016a). Are there too many uncited articles? Zero inflated variants of the discretised lognormal and hooked power law distributions. Journal of Informetrics, 10(2), 622–633. doi:10.1016/j.joi.2016.04.014.

    Article  Google Scholar 

  • Thelwall, M. (2016b). Interpreting correlations between citation counts and other indicators. Scientometrics, 108(1), 337–347. doi:10.1007/s11192-016-1973-7.

    Article  Google Scholar 

  • Thelwall, M. (2017a). Are Mendeley reader counts high enough for research evaluations when articles are published? Aslib Journal of Information Management, 69(2), 174–183. doi:10.1108/AJIM-01-2017-0028.

    Article  Google Scholar 

  • Thelwall, M. (2017b). Three practical field normalised alternative indicator formulae for research evaluation. Journal of Informetrics, 11(1), 128–151. doi:10.1016/j.joi.2016.12.002.

    Article  Google Scholar 

  • Thelwall, M., & Fairclough, R. (2015). Geometric journal impact factors correcting for individual highly cited articles. Journal of Informetrics, 9(2), 263–272.

    Article  Google Scholar 

  • Thelwall, M., & Maflahi, N. (2015). Are scholarly articles disproportionately read in their own country? An analysis of Mendeley readers. Journal of the Association for Information Science and Technology, 66(6), 1124–1135. doi:10.1002/asi.23252.

    Article  Google Scholar 

  • Thelwall, M., & Sud, P. (2016). Mendeley readership counts: An investigation of temporal and disciplinary differences. Journal of the Association for Information Science and Technology, 57(6), 3036–3050. doi:10.1002/asi.2355.

    Article  Google Scholar 

  • Thelwall, M., & Wilson, P. (2016). Mendeley readership altmetrics for medical articles: An analysis of 45 fields. Journal of the Association for Information Science and Technology, 67(8), 1962–1972. doi:10.1002/asi.23501.

    Article  Google Scholar 

  • Van Noorden, R. (2014). Scientists and the social networks. Nature, 512(7513), 126–130.

    Article  Google Scholar 

  • van Raan, A. F. (2006). Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups. Scientometrics, 67(3), 491–502.

    Article  Google Scholar 

  • Waltman, L., van Eck, N. J., van Leeuwen, T. N., Visser, M. S., & van Raan, A. F. (2011). Towards a new crown indicator: An empirical analysis. Scientometrics, 87(3), 467–481.

    Article  Google Scholar 

  • Wang, Q., & Waltman, L. (2016). Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus. Journal of Informetrics, 10(2), 347–364.

    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.

  • Wouters, P., & Costas, R. (2012). Users, narcissism and control: Tracking the impact of scholarly publications in the 21st century. In: E. Archambault, Y. Gingras, & V. Larivière (Eds) Proceedings of the 17th international conference on science and technology indicators (Vol. 2, pp. 487–497). Montreal: Science-Metrix and OST.

  • Zahedi, Z., Costas, R., & Wouters, P. (2014a). How well developed are altmetrics? A crossdisciplinary analysis of the presence of ‘alternative metrics’ in scientific publications. Scientometrics, 101(2), 1491–1513.

    Article  Google Scholar 

  • Zahedi, Z., Costas, R., & Wouters, P. (2017). Mendeley readership as a filtering tool to identify highly cited publications. Journal of the Association for Information Science and Technology, 68(10), 2511–2521.

    Article  Google Scholar 

  • Zahedi, Z., Haustein, S. & Bowman, T. (2014b). Exploring data quality and retrieval strategies for Mendeley reader counts. Presentation at SIGMET Metrics 2014 workshop, 5 November 2014. Available: http://www.slideshare.net/StefanieHaustein/sigmetworkshop-asist2014.

  • Zitt, M. (2012). The journal impact factor: Angel, devil, or scapegoat? A comment on JK Vanclay’s article 2011. Scientometrics, 92(2), 485–503.

    Article  Google Scholar 

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Correspondence to Mike Thelwall.

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Thelwall, M. Are Mendeley reader counts useful impact indicators in all fields?. Scientometrics 113, 1721–1731 (2017). https://doi.org/10.1007/s11192-017-2557-x

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