, Volume 98, Issue 3, pp 1923–1933 | Cite as

Usage history of scientific literature: Nature metrics and metrics of Nature publications

  • Xianwen Wang
  • Wenli Mao
  • Shenmeng Xu
  • Chunbo Zhang


In this study, we analyze the dynamic usage history of Nature publications over time using Nature metrics data. We conduct analysis from two perspectives. On the one hand, we examine how long it takes before the articles’ downloads reach 50 %/80 % of the total; on the other hand, we compare the percentage of total downloads in 7, 30, and 100 days after publication. In general, papers are downloaded most frequently within a short time period right after their publication. And we find that compared with non-Open Access papers, readers’ attention on Open Access publications are more enduring. Based on the usage data of a newly published paper, regression analysis could predict the future expected total usage counts.


Altmetrics Article-level metrics Download Nature metrics Page view Usage data 



The work was supported by the project of “National Natural Science Foundation of China” (61301227), “Social Science Foundation of China” (10CZX011) and the project of “Fundamental Research Funds for the Central Universities” (DUT12RW309).


  1. Bollen, J., & Luce, R. (2002). Evaluation of digital library impact and user communities by analysis of usage patterns. D-Lib Magazine, 8(6), 1–13.CrossRefGoogle Scholar
  2. 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
  3. Davis, P. M., Lewenstein, B. V., Simon, D. H., Booth, J. G., & Connolly, M. J. L. (2008). Open access publishing, article downloads, and citations: randomised controlled trial. BMJ, 337, a56.Google Scholar
  4. Davis, P. M., & Price, J. S. (2006). eJournal interface can influence usage statistics: implications for libraries, publishers, and Project COUNTER. Journal of the American Society for Information Science and Technology, 57(9), 1243–1248.CrossRefGoogle Scholar
  5. Davis, P. M., & Solla, L. R. (2003). An IP-level analysis of usage statistics for electronic journals in chemistry: Making inferences about user behavior. Journal of the American Society for Information Science and Technology, 54(11), 1062–1068.CrossRefGoogle Scholar
  6. Galligan, F., & Dyas-Correia, S. (2013). Altmetrics: Rethinking the Way We measure. Serials Review, 39(1), 56–61.CrossRefGoogle Scholar
  7. Henneken, E. A., Eichhorn, G., Accomazzi, A., Kurtz, M. J., Grant, C., Thompson, D., et al. (2010). How the literature is used a view through citation and usage statistics of the ADS. In Proceedings of the Third UN/ESA/NASA Workshop on the International Heliophysical Year 2007 and Basic Space Science (pp. 141–147). Berlin, Springer.Google Scholar
  8. Henneken, E. A., Kurtz, M. J., Accomazzi, A., Grant, C. S., Thompson, D., Bohlen, E., et al. (2009). Use of astronomical literature—A report on usage patterns. Journal of Informetrics, 3(1), 1–8.CrossRefGoogle Scholar
  9. ImpactStory. (2012). A new framework for altmetrics. Accessed 29 Oct 2013.
  10. Kaplan, N. R., & Nelson, M. L. (2000). Determining the publication impact of a digital library. Journal of the American society for information science, 51(4), 324–339.CrossRefGoogle Scholar
  11. Kousha, K., Thelwall, M., & Rezaie, S. (2010). Using the web for research evaluation: the integrated online impact indicator. Journal of Informetrics, 4(1), 124–135.CrossRefGoogle Scholar
  12. Kurtz, M. J., Eichhorn, G., Accomazzi, A., Grant, C., Demleitner, M., & Murray, S. S. (2005a). Worldwide use and impact of the NASA Astrophysics Data System digital library. Journal of the American Society for Information Science and Technology, 56(1), 36–45.CrossRefGoogle Scholar
  13. Kurtz, M. J., Eichhorn, G., Accomazzi, A., Grant, C., Demleitner, M., Murray, S. S., et al. (2005b). The bibliometric properties of article readership information. Journal of the American Society for Information Science and Technology, 56(2), 111–128.CrossRefGoogle Scholar
  14. Lin, J., & Fenner, M. (2013). Altmetrics in Eeolution: Defining & redefining the ontology of article-level metrics. Information Standards Quarterly, 25(2), 20.CrossRefGoogle Scholar
  15. Marek, K., & Valauskas, E. J. (2002). Web logs as indices of electronic journal use: Tools for identifying a “classic” article. Libri, 52(4), 220–230.CrossRefGoogle Scholar
  16. Nature. (2012). Nature metrics. Nature, 491(7422), 8. doi: 10.1038/491008b.
  17. Priem, J., & Hemminger, B. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7). doi: 10.5210/fm.v15i7.2874.
  18. Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2010). Altmetrics: A manifesto. Accessed 29 Oct 2013.
  19. Shuai, X., Pepe, A., & Bollen, J. (2012). How the scientific community reacts to newly submitted preprints: article downloads, Twitter mentions, and citations. arXiv preprint arXiv:1202.2461.Google Scholar
  20. Thelwall, M. (2008). Bibliometrics to webometrics. Journal of information science, 34(4), 605–621.CrossRefGoogle Scholar
  21. Thelwall, M. (2012). Journal impact evaluation: A webometric perspective. Scientometrics, 92(2), 429–441.CrossRefGoogle Scholar
  22. Wang, X., Peng, L., Zhang, C., Xu, S., Wang, Z., Wang, C., et al. (2013). Exploring scientists’ working timetable: A global survey. Journal of Informetrics, 7(3), 665–675.CrossRefGoogle Scholar
  23. Wang, X., Wang, Z., & Xu, S. (2012a). Tracing scientist’s research trends realtimely. Scientometrics, 95(2), 717–729.CrossRefGoogle Scholar
  24. Wang, X., Xu, S., Peng, L., Wang, Z., Wang, C., Zhang, C., et al. (2012b). Exploring scientists’ working timetable: Do scientists often work overtime? Journal of Informetrics, 6(4), 655–660.CrossRefzbMATHGoogle Scholar
  25. Wei, J., Bu, B., & Liang, L. (2012). Estimating the diffusion models of crisis information in micro blog. Journal of Informetrics, 6(4), 600–610.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2013

Authors and Affiliations

  • Xianwen Wang
    • 1
    • 2
  • Wenli Mao
    • 1
  • Shenmeng Xu
    • 3
  • Chunbo Zhang
    • 1
  1. 1.WISE Lab, School of Public Administration and LawDalian University of TechnologyDalianChina
  2. 2.DUT-Drexel Joint Institute for the Study of Knowledge Visualization and Scientific DiscoveryDalian University of TechnologyDalianChina
  3. 3.School of Information and Library ScienceUniversity of North Carolina at Chapel HillChapel HillUSA

Personalised recommendations