IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i5d10.1007_s11192-023-04676-8.html
   My bibliography  Save this article

The rise of hyperprolific authors in computer science: characterization and implications

Author

Listed:
  • Edré Moreira

    (Universidade Federal de Minas Gerais)

  • Wagner Meira

    (Universidade Federal de Minas Gerais)

  • Marcos André Gonçalves

    (Universidade Federal de Minas Gerais)

  • Alberto H. F. Laender

    (Universidade Federal de Minas Gerais)

Abstract

In this article we study and characterize the phenomenon of the hyperprolific authors, who are the most productive researchers according to a given repository in a specific period of time. Particularly, we are interested in investigating and characterizing a subset of such hyperprolific authors who present a sudden growth in the number of published articles and coauthors, as well as concentrate their publications in a few specific journals, what can be seen as an anomalous behavior. Using data collected from the DBLP repository and covering the last 10 years, we propose a set of discriminative dimensions (features) aimed at characterizing the behavior of hyperprolific authors, ultimately helping to identify anomalous ones. Moreover, using a strategy based on ranking aggregation to identify the most prominent anomalous authors, we demonstrate that the best dimensions to characterize such anomalous behaviors may vary significantly among authors, but it is possible to identify a clear subset of them who present such behavior. Our results show that the top-ranked (most anomalous) authors manifest a distinct behavior from the middle-ranked ones. Indeed, each one of the five most anomalous authors published more than 48 journal articles in 2021 while collaborating with more than 1,000 coauthors in their careers. Specifically, one of such authors published more than 140 articles in just a single journal.

Suggested Citation

  • Edré Moreira & Wagner Meira & Marcos André Gonçalves & Alberto H. F. Laender, 2023. "The rise of hyperprolific authors in computer science: characterization and implications," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2945-2974, May.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04676-8
    DOI: 10.1007/s11192-023-04676-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04676-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-023-04676-8?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.

    References listed on IDEAS

    as
    1. Agnes Grudniewicz & David Moher & Kelly D. Cobey & Gregory L. Bryson & Samantha Cukier & Kristiann Allen & Clare Ardern & Lesley Balcom & Tiago Barros & Monica Berger & Jairo Buitrago Ciro & Lucia Cug, 2019. "Predatory journals: no definition, no defence," Nature, Nature, vol. 576(7786), pages 210-212, December.
    2. Sven Helmer & David B. Blumenthal & Kathrin Paschen, 2020. "What is meaningful research and how should we measure it?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 153-169, October.
    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.
    4. Weihua Li & Tomaso Aste & Fabio Caccioli & Giacomo Livan, 2019. "Early coauthorship with top scientists predicts success in academic careers," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    5. Declan Butler, 2008. "Free journal-ranking tool enters citation market," Nature, Nature, vol. 451(7174), pages 6-6, January.
    6. Harlley Lima & Thiago H. P. Silva & Mirella M. Moro & Rodrygo L. T. Santos & Wagner Meira & Alberto H. F. Laender, 2015. "Assessing the profile of top Brazilian computer science researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 879-896, June.
    7. Pan, Raj K. & Petersen, Alexander M. & Pammolli, Fabio & Fortunato, Santo, 2018. "The memory of science: Inflation, myopia, and the knowledge network," Journal of Informetrics, Elsevier, vol. 12(3), pages 656-678.
    8. Mario Biagioli, 2016. "Watch out for cheats in citation game," Nature, Nature, vol. 535(7611), pages 201-201, July.
    9. Felipe Viegas & Antônio Pereira & Pablo Cecílio & Elisa Tuler & Wagner Meira & Marcos Gonçalves & Leonardo Rocha, 2022. "Semantic Academic Profiler (SAP): a framework for researcher assessment based on semantic topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 5005-5026, August.
    Full references (including those not matched with items on IDEAS)

    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. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    2. Jaime A. Teixeira da Silva & Quan-Hoang Vuong, 2021. "The right to refuse unwanted citations: rethinking the culture of science around the citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5355-5360, June.
    3. Darrin J. Griffin & Zachary W. Arth & Samuel D. Hakim & Brian C. Britt & James N. Gilbreath & Mackenzie P. Pike & Andrew J. Laningham & Fareed Bordbar & Sage Hart & San Bolkan, 2021. "Collaborations in communication: Authorship credit allocation via a weighted fractional count procedure," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4355-4372, May.
    4. 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).
    5. Bodil Hoffmeyer & Siv Fonnes & Kristoffer Andresen & Jacob Rosenberg, 2023. "Use of inactive Cochrane reviews in academia: A citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2923-2934, May.
    6. Jeppe Nicolaisen & Tove Faber Frandsen, 2021. "Number of references: a large-scale study of interval ratios," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 259-285, January.
    7. Batista-Jr, Antônio de Abreu & Gouveia, Fábio Castro & Mena-Chalco, Jesús P., 2021. "Predicting the Q of junior researchers using data from the first years of publication," Journal of Informetrics, Elsevier, vol. 15(2).
    8. Lu, Wei & Ren, Yan & Huang, Yong & Bu, Yi & Zhang, Yuehan, 2021. "Scientific collaboration and career stages: An ego-centric perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    9. Wu, Jiang & Ou, Guiyan & Liu, Xiaohui & Dong, Ke, 2022. "How does academic education background affect top researchers’ performance? Evidence from the field of artificial intelligence," Journal of Informetrics, Elsevier, vol. 16(2).
    10. 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.
    11. Sarah Shandera & Jes L Matsick & David R Hunter & Louis Leblond, 2021. "RASE: Modeling cumulative disadvantage due to marginalized group status in academia," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-20, December.
    12. Ying Guo & Xiantao Xiao, 2022. "Author-level altmetrics for the evaluation of Chinese scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 973-990, February.
    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. Adrian G Barnett & Pauline Zardo & Nicholas Graves, 2018. "Randomly auditing research labs could be an affordable way to improve research quality: A simulation study," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-17, April.
    16. 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.
    17. Carolina Llorente & Gema Revuelta, 2023. "Models of Teaching Science Communication," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    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. Zoltán Krajcsák, 2021. "Researcher Performance in Scopus Articles ( RPSA ) as a New Scientometric Model of Scientific Output: Tested in Business Area of V4 Countries," Publications, MDPI, vol. 9(4), pages 1-23, October.
    20. Neal R. Haddaway & Max W. Callaghan & Alexandra M. Collins & William F. Lamb & Jan C. Minx & James Thomas & Denny John, 2020. "On the use of computer‐assistance to facilitate systematic mapping," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(4), December.

    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:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04676-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.