IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i6d10.1007_s11192-022-04359-w.html
   My bibliography  Save this article

Modeling the obsolescence of research literature in disciplinary journals through the age of their cited references

Author

Listed:
  • Pablo Dorta-González

    (University of Las Palmas de Gran Canaria)

  • Emilio Gómez-Déniz

    (University of Las Palmas de Gran Canaria)

Abstract

There are different citation habits in the research fields that influence the obsolescence of the research literature. We analyze the distinctive obsolescence of research literature in disciplinary journals in eight scientific subfields based on cited references distribution, as a synchronous approach. We use both negative binomial (NB) and Poisson distributions to capture this obsolescence. The corpus being examined is published in 2019 and covers 22,559 papers citing 872,442 references. Moreover, three measures to analyze the tail of the distribution are proposed: (i) cited reference survival rate, (ii) cited reference mortality rate, and (iii) cited reference percentile. These measures are interesting because the tail of the distribution collects the behavior of the citations at the time when the document starts to get obsolete in the sense that it is little cited (used). As main conclusion, the differences observed in obsolescence are so important even between disciplinary journals in the same subfield, that it would be necessary to use some measure for the tail of the citation distribution, such as those proposed in this paper, when analyzing in an appropriate way the long time impact of a journal.

Suggested Citation

  • Pablo Dorta-González & Emilio Gómez-Déniz, 2022. "Modeling the obsolescence of research literature in disciplinary journals through the age of their cited references," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 2901-2931, June.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:6:d:10.1007_s11192-022-04359-w
    DOI: 10.1007/s11192-022-04359-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04359-w
    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/s11192-022-04359-w?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. Hamid Bouabid & Vincent Larivière, 2013. "The lengthening of papers’ life expectancy: a diachronous analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 695-717, December.
    2. Mingyang Wang & Jiaqi Zhang & Guangsheng Chen & Kah-Hin Chai, 2019. "Examining the influence of open access on journals’ citation obsolescence by modeling the actual citation process," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1621-1641, June.
    3. R. E. Burton & R. W. Kebler, 1960. "The “half‐life” of some scientific and technical literatures," American Documentation, Wiley Blackwell, vol. 11(1), pages 18-22, January.
    4. Leo Egghe & Ronald Rousseau, 2000. "The influence of publication delays on the observed aging distribution of scientific literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(2), pages 158-165.
    5. Lin Zhang & Wolfgang Glänzel, 2017. "A citation-based cross-disciplinary study on literature ageing: part II—diachronous aspects," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1559-1572, June.
    6. Vincent Larivière & Éric Archambault & Yves Gingras, 2008. "Long‐term variations in the aging of scientific literature: From exponential growth to steady‐state science (1900–2004)," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(2), pages 288-296, January.
    7. Hamid Bouabid, 2011. "Revisiting citation aging: a model for citation distribution and life-cycle prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 199-211, July.
    8. B. C. Brookes, 1970. "Obsolescence of special library periodicals: Sampling errors and utility contours," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 21(5), pages 320-329, September.
    9. Quentin L. Burrell, 2002. "The nth-citation distribution and obsolescence," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 309-323, March.
    10. Usha Gupta, 1990. "Obsolescence of physics literature: Exponential decrease of the density of citations to Physical Review articles with age," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(4), pages 282-287, June.
    11. Leo Egghe & I. K. R. Ravichandra Rao, 2002. "Theory and experimentation on the most-recent-reference distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 371-387, March.
    12. Yanhui Song & Feng Ma & Siluo Yang, 2015. "Comparative study on the obsolescence of humanities and social sciences in China: under the new situation of web," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 365-388, January.
    13. Lin Zhang & Wolfgang Glänzel, 2017. "A citation-based cross-disciplinary study on literature aging: part I—the synchronous approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1573-1589, June.
    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. González-Betancor, Sara M. & Dorta-González, Pablo, 2023. "Does society show differential attention to researchers based on gender and field?," Journal of Informetrics, Elsevier, vol. 17(4).
    2. Gómez-Déniz, Emilio & Dorta-González, Pablo, 2024. "Modeling citation concentration through a mixture of Leimkuhler curves," Journal of Informetrics, Elsevier, vol. 18(2).

    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. Mingyang Wang & Jiaqi Zhang & Guangsheng Chen & Kah-Hin Chai, 2019. "Examining the influence of open access on journals’ citation obsolescence by modeling the actual citation process," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1621-1641, June.
    2. 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.
    3. Hamid Bouabid & Vincent Larivière, 2013. "The lengthening of papers’ life expectancy: a diachronous analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 695-717, December.
    4. Aaron Lercher & Lawrence Smolinsky, 2016. "Persistent value of older scientific journal articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1205-1220, September.
    5. Staša Milojević, 2012. "How Are Academic Age, Productivity and Collaboration Related to Citing Behavior of Researchers?," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-13, November.
    6. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    7. Fabio S. V. Silva & Peter A. Schulz & Everard C. M. Noyons, 2019. "Co-authorship networks and research impact in large research facilities: benchmarking internal reports and bibliometric databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 93-108, January.
    8. Shahzad, Murtuza & Alhoori, Hamed & Freedman, Reva & Rahman, Shaikh Abdul, 2022. "Quantifying the online long-term interest in research," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Ugo Finardi, 2017. "Long time series of highly cited articles: an empirical study," IRCrES Working Paper 201712, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    10. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    11. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    12. Liang, Guoqiang & Hou, Haiyan & Ding, Ying & Hu, Zhigang, 2020. "Knowledge recency to the birth of Nobel Prize-winning articles: Gender, career stage, and country," Journal of Informetrics, Elsevier, vol. 14(3).
    13. Pei-Shan Chi & Wolfgang Glänzel, 2022. "An article-based cross-disciplinary study of reference literature for indicator improvement," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7077-7089, December.
    14. Lin Zhang & Wolfgang Glänzel, 2017. "A citation-based cross-disciplinary study on literature ageing: part II—diachronous aspects," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1559-1572, June.
    15. Zhenyu Gou & Fan Meng & Zaida Chinchilla-Rodríguez & Yi Bu, 2022. "Encoding the citation life-cycle: the operationalization of a literature-aging conceptual model," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 5027-5052, August.
    16. Mingyang Wang & Shi Li & Guangsheng Chen, 2017. "Detecting latent referential articles based on their vitality performance in the latest 2 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1557-1571, September.
    17. Finardi, Ugo, 2014. "On the time evolution of received citations, in different scientific fields: An empirical study," Journal of Informetrics, Elsevier, vol. 8(1), pages 13-24.
    18. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    19. Sangwal, Keshra, 2015. "On the growth dynamics of citations of articles by some Nobel Prize winners," Journal of Informetrics, Elsevier, vol. 9(3), pages 466-476.
    20. Diana Hicks & Julia Melkers & Kimberley R. Isett, 2019. "A characterization of professional media and its links to research," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 827-843, May.

    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:127:y:2022:i:6:d:10.1007_s11192-022-04359-w. 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.