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The relationship between usage and citations in an open access mega-journal

Author

Listed:
  • Barbara McGillivray

    (The Alan Turing Institute
    University of Cambridge)

  • Mathias Astell

    (Hindawi Limited)

Abstract

How do the level of usage of an article, the timeframe of its usage and its subject area relate to the number of citations it accrues? This paper aims to answer this question through an observational study of usage and citation data collected about the multidisciplinary, open access mega-journal Scientific Reports. This observational study answers these questions using the following methods: an overlap analysis of most read and top-cited articles; Spearman correlation tests between total citation counts over two years and usage over various timeframes; a comparison of first months of citation for most read and all articles; a Wilcoxon test on the distribution of total citations of early cited articles and the distribution of total citations of all other articles. All analyses were performed in using the programming language R. As Scientific Reports is a multidisciplinary journal covering all natural and clinical sciences, we also looked at the differences across subjects. We found a moderate correlation between usage in the first year and citations in the first two years since publication (Spearman correlation coefficient of 0.49, α = 0.05), and that articles with high usage in the first six months are more likely to have their first citation earlier (Wilcoxon = 1,811,500, p

Suggested Citation

  • Barbara McGillivray & Mathias Astell, 2019. "The relationship between usage and citations in an open access mega-journal," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 817-838, November.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:2:d:10.1007_s11192-019-03228-3
    DOI: 10.1007/s11192-019-03228-3
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    References listed on IDEAS

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    Cited by:

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    3. Yang Ding & Xianlei Dong & Yi Bu & Bin Zhang & Kexin Lin & Beibei Hu, 2021. "Revisiting the relationship between downloads and citations: a perspective from papers with different citation patterns in the case of the Lancet," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7609-7621, September.
    4. Lin Zhang & Beibei Sun & Fei Shu & Ying Huang, 2022. "Comparing paper level classifications across different methods and systems: an investigation of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7633-7651, December.
    5. Andrés Fernández-Ramos & Blanca Rodríguez-Bravo & Ángela Diez-Diez, 2023. "Use of scientific journals in Spanish universities: analysis of the relationship between citations and downloads in two university library consortia," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2489-2505, April.
    6. Łukasz Wiechetek & Zbigniew Pastuszak, 2022. "Academic social networks metrics: an effective indicator for university performance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1381-1401, March.
    7. Mingkun Wei & Abdolreza Noroozi Chakoli, 2020. "Evaluating the relationship between the academic and social impact of open access books based on citation behaviors and social media attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2401-2420, December.

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