IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v391y2012i5p2129-2134.html
   My bibliography  Save this article

A scaling between Impact Factor and uncitedness

Author

Listed:
  • Hsu, Jiann-wien
  • Huang, Ding-wei

Abstract

The Impact Factor has become a well-known measure of the average citation number of articles published in a scientific journal. A journal with a high Impact Factor is assumed to have a low percentage of uncited articles. We show that the scaling relation between the Impact Factor and the uncited percentage can be understood by a simple mechanism. The empirical data can be reproduced by a random mechanism with the cumulative advantage. To further explore the robustness of such a mechanism, we investigate the relation between the average citation number and the uncited percentage from different perspectives. We apply the idea of Impact Factor to the publications of an institute in addition to its general application to the publications of a journal. We find that the same scaling relation can be obtained. We also show that a static relation can be applied to describe the time evolution of a dynamical process. These results provide further justification for the same citation mechanism behind different research fields.

Suggested Citation

  • Hsu, Jiann-wien & Huang, Ding-wei, 2012. "A scaling between Impact Factor and uncitedness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2129-2134.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:5:p:2129-2134
    DOI: 10.1016/j.physa.2011.11.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437111008636
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2011.11.028?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianhua Hou & Jiantao Ye, 2020. "Are uncited papers necessarily all nonimpact papers? A quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1631-1662, August.
    2. Katchanov, Yurij L. & Markova, Yulia V. & Shmatko, Natalia A., 2023. "Uncited papers in the structure of scientific communication," Journal of Informetrics, Elsevier, vol. 17(2).
    3. Lucio Bertoli-Barsotti & Tommaso Lando, 2017. "A theoretical model of the relationship between the h-index and other simple citation indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1415-1448, June.
    4. Javier E., Contreras-Reyes, 2016. "Credit allocation based on journal impact factor and coauthorship contribution," MPRA Paper 71294, University Library of Munich, Germany.
    5. Hu, Zewen & Wu, Yishan, 2014. "Regularity in the time-dependent distribution of the percentage of never-cited papers: An empirical pilot study based on the six journals," Journal of Informetrics, Elsevier, vol. 8(1), pages 136-146.
    6. Zewen Hu & Yishan Wu & Jianjun Sun, 2018. "A quantitative analysis of determinants of non-citation using a panel data model," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 843-861, August.
    7. Lucio Bertoli-Barsotti & Tommaso Lando, 2017. "The h-index as an almost-exact function of some basic statistics," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1209-1228, November.
    8. Egghe, L., 2013. "The functional relation between the impact factor and the uncitedness factor revisited," Journal of Informetrics, Elsevier, vol. 7(1), pages 183-189.
    9. Jeppe Nicolaisen & Tove Faber Frandsen, 2019. "Zero impact: a large-scale study of uncitedness," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1227-1254, May.
    10. Burrell, Quentin L., 2013. "A stochastic approach to the relation between the impact factor and the uncitedness factor," Journal of Informetrics, Elsevier, vol. 7(3), pages 676-682.
    11. Pablo Dorta-González & Rafael Suárez-Vega & María Isabel Dorta-González, 2020. "Open access effect on uncitedness: a large-scale study controlling by discipline, source type and visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2619-2644, September.
    12. Javier E. Contreras-Reyes, 2016. "Credit allocation based on journal impact factor and coauthorship contribution," Papers 1606.04139, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:391:y:2012:i:5:p:2129-2134. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.