IDEAS home Printed from https://ideas.repec.org/a/gam/jpubli/v5y2017i3p20-d106517.html
   My bibliography  Save this article

Improving the Measurement of Scientific Success by Reporting a Self-Citation Index

Author

Listed:
  • Justin W. Flatt

    (Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland)

  • Alessandro Blasimme

    (Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Effy Vayena

    (Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

Abstract

Who among the many researchers is most likely to usher in a new era of scientific breakthroughs? This question is of critical importance to universities, funding agencies, as well as scientists who must compete under great pressure for limited amounts of research money. Citations are the current primary means of evaluating one’s scientific productivity and impact, and while often helpful, there is growing concern over the use of excessive self-citations to help build sustainable careers in science. Incorporating superfluous self-citations in one’s writings requires little effort, receives virtually no penalty, and can boost, albeit artificially, scholarly impact and visibility, which are both necessary for moving up the academic ladder. Such behavior is likely to increase, given the recent explosive rise in popularity of web-based citation analysis tools (Web of Science, Google Scholar, Scopus, and Altmetric) that rank research performance. Here, we argue for new metrics centered on transparency to help curb this form of self-promotion that, if left unchecked, can have a negative impact on the scientific workforce, the way that we publish new knowledge, and ultimately the course of scientific advance.

Suggested Citation

  • Justin W. Flatt & Alessandro Blasimme & Effy Vayena, 2017. "Improving the Measurement of Scientific Success by Reporting a Self-Citation Index," Publications, MDPI, vol. 5(3), pages 1-6, August.
  • Handle: RePEc:gam:jpubli:v:5:y:2017:i:3:p:20-:d:106517
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2304-6775/5/3/20/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2304-6775/5/3/20/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. J. E. Hirsch, 2010. "An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 741-754, December.
    2. Christoph Bartneck & Servaas Kokkelmans, 2011. "Detecting h-index manipulation through self-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 85-98, April.
    3. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Yuetong Chen & Hao Wang & Baolong Zhang & Wei Zhang, 2022. "A method of measuring the article discriminative capacity and its distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3317-3341, June.
    2. Stefano Vercelli & Leonardo Pellicciari & Andrea Croci & Cesare Maria Cornaggia & Francesca Cecchi & Daniele Piscitelli, 2023. "Self-citation behavior within the health allied professions’ scientific sector in Italy: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1205-1217, February.
    3. Fabio Zagonari, 2019. "Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined," Publications, MDPI, vol. 7(2), pages 1-30, May.
    4. Ameni Kacem & Justin W. Flatt & Philipp Mayr, 2020. "Tracking self-citations in academic publishing," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1157-1165, May.
    5. Margaret K. Merga & Sayidi Mat Roni & Shannon Mason, 2020. "Should Google Scholar be used for benchmarking against the professoriate in education?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2505-2522, December.
    6. Abramo, Giovanni & D'Angelo, Ciriaco Andrea & Grilli, Leonardo, 2021. "The effects of citation-based research evaluation schemes on self-citation behavior," Journal of Informetrics, Elsevier, vol. 15(4).
    7. Esther Salmerón-Manzano & Francisco Manzano-Agugliaro, 2017. "Worldwide Scientific Production Indexed by Scopus on Labour Relations," Publications, MDPI, vol. 5(4), pages 1-14, October.
    8. B. Preedip Balaji & M. Dhanamjaya, 2019. "Preprints in Scholarly Communication: Re-Imagining Metrics and Infrastructures," Publications, MDPI, vol. 7(1), pages 1-23, January.
    9. Gordana Budimir & Sophia Rahimeh & Sameh Tamimi & Primož Južnič, 2021. "Comparison of self-citation patterns in WoS and Scopus databases based on national scientific production in Slovenia (1996–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2249-2267, March.
    10. T. Liskiewicz & G. Liskiewicz & J. Paczesny, 2021. "Factors affecting the citations of papers in tribology journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3321-3336, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lei Li & Yan Wang & Guanfeng Liu & Meng Wang & Xindong Wu, 2015. "Context-Aware Reviewer Assignment for Trust Enhanced Peer Review," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-28, June.
    2. Asma Hammami & Nabil Semmar, 2022. "The simplex simulation as a tool to reveal publication strategies and citation factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 319-350, January.
    3. Maurice Poirrier & Sebastián Moreno & Gonzalo Huerta-Cánepa, 2021. "Robust h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1969-1981, March.
    4. Antonio Fernandez-Cano & Inés M. Fernández-Guerrero, 2017. "A multivariate model for evaluating emergency medicine journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 991-1003, February.
    5. Rabishankar Giri & Sabuj Kumar Chaudhuri, 2021. "Ranking journals through the lens of active visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2189-2208, March.
    6. Yingjin Song & Ruiyi Li & Guanyi Chen & Beibei Yan & Lei Zhong & Yuxin Wang & Yihang Li & Jinlei Li & Yingxiu Zhang, 2021. "Bibliometric Analysis of Current Status on Bioremediation of Petroleum Contaminated Soils during 2000–2019," IJERPH, MDPI, vol. 18(16), pages 1-20, August.
    7. Vîiu, Gabriel-Alexandru, 2016. "A theoretical evaluation of Hirsch-type bibliometric indicators confronted with extreme self-citation," Journal of Informetrics, Elsevier, vol. 10(2), pages 552-566.
    8. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    9. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    10. Ash Mohammad Abbas, 2011. "Weighted indices for evaluating the quality of research with multiple authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 107-131, July.
    11. Jiang Wu, 2013. "Geographical knowledge diffusion and spatial diversity citation rank," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 181-201, January.
    12. Ramona Weinrich, 2019. "Opportunities for the Adoption of Health-Based Sustainable Dietary Patterns: A Review on Consumer Research of Meat Substitutes," Sustainability, MDPI, vol. 11(15), pages 1-15, July.
    13. Piers Steel & Sjoerd Beugelsdijk & Herman Aguinis, 2021. "The anatomy of an award-winning meta-analysis: Recommendations for authors, reviewers, and readers of meta-analytic reviews," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(1), pages 23-44, February.
    14. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    15. Daniele Checchi & Alberto Ciolfi & Gianni De Fraja & Irene Mazzotta & Stefano Verzillo, 2021. "Have you Read This? An Empirical Comparison of the British REF Peer Review and the Italian VQR Bibliometric Algorithm," Economica, London School of Economics and Political Science, vol. 88(352), pages 1107-1129, October.
    16. Hui Li & Weishu Liu, 2020. "Same same but different: self-citations identified through Scopus and Web of Science Core Collection," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2723-2732, September.
    17. Augusteijn, Hilde Elisabeth Maria & van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2021. "Posterior Probabilities of Effect Sizes and Heterogeneity in Meta-Analysis: An Intuitive Approach of Dealing with Publication Bias," OSF Preprints avkgj, Center for Open Science.
    18. Ruhua Huang & Yuting Huang & Fan Qi & Leyi Shi & Baiyang Li & Wei Yu, 2022. "Exploring the characteristics of special issues: distribution, topicality, and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5233-5256, September.
    19. M. Ausloos, 2013. "A scientometrics law about co-authors and their ranking: the co-author core," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 895-909, June.
    20. Lathabai, Hiran H., 2020. "ψ-index: A new overall productivity index for actors of science and technology," Journal of Informetrics, Elsevier, vol. 14(4).

    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:gam:jpubli:v:5:y:2017:i:3:p:20-:d:106517. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.