IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v3y2009i4p296-303.html
   My bibliography  Save this article

Modeling a century of citation distributions

Author

Listed:
  • Wallace, Matthew L.
  • Larivière, Vincent
  • Gingras, Yves

Abstract

The prevalence of uncited papers or of highly cited papers, with respect to the bulk of publications, provides important clues as to the dynamics of scientific research. Using 25 million papers and 600 million references from the Web of Science over the 1900–2006 period, this paper proposes a simple model based on a random selection process to explain the “uncitedness” phenomenon and its decline over the years. We show that the proportion of cited papers is a function of (1) the number of articles available (the competing papers), (2) the number of citing papers and (3) the number of references they contain. Using uncitedness as a departure point, we demonstrate the utility of the stretched-exponential function and a form of the Tsallis q-exponential function to fit complete citation distributions over the 20th century. As opposed to simple power-law fits, for instance, both these approaches are shown to be empirically well-grounded and robust enough to better understand citation dynamics at the aggregate level. On the basis of these models, we provide quantitative evidence and provisional explanations for an important shift in citation practices around 1960. We also propose a revision of the “citation classic” category as a set of articles which is clearly distinguishable from the rest of the field.

Suggested Citation

  • Wallace, Matthew L. & Larivière, Vincent & Gingras, Yves, 2009. "Modeling a century of citation distributions," Journal of Informetrics, Elsevier, vol. 3(4), pages 296-303.
  • Handle: RePEc:eee:infome:v:3:y:2009:i:4:p:296-303
    DOI: 10.1016/j.joi.2009.03.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157709000327
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joi.2009.03.010?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. Vincent Larivière & Éric Archambault & Yves Gingras & Étienne Vignola‐Gagné, 2006. "The place of serials in referencing practices: Comparing natural sciences and engineering with social sciences and humanities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(8), pages 997-1004, June.
    2. Leo Egghe, 2000. "A Heuristic Study of the First-Citation Distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(3), pages 345-359, July.
    3. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
    4. Anthony F. J. van Raan, 2000. "On Growth, Ageing, and Fractal Differentiation of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 347-362, February.
    5. Péter Vinkler, 2002. "Dynamic changes in the chance for citedness," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 421-434, July.
    6. Anthony F.J. van Raan, 2006. "Statistical properties of bibliometric indicators: Research group indicator distributions and correlations," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 408-430, February.
    7. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    8. Richard E. Stern, 1990. "Uncitedness in the biomedical literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(3), pages 193-196, April.
    9. Derek De Solla Price, 1976. "A general theory of bibliometric and other cumulative advantage processes," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(5), pages 292-306, September.
    10. Gupta, Hari M. & Campanha, José R. & Schinaider, Sidney J., 2008. "Size limiting in Tsallis statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6745-6751.
    11. Mikhail V. Simkin & Vwani P. Roychowdhury, 2007. "A mathematical theory of citing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1661-1673, September.
    12. Quentin L. Burrell, 2002. "The nth-citation distribution and obsolescence," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 309-323, March.
    13. Hendrik P. van Dalen & Kène Henkens, 2004. "Demographers and Their Journals: Who Remains Uncited After Ten Years?," Population and Development Review, The Population Council, Inc., vol. 30(3), pages 489-506, September.
    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. Thelwall, Mike, 2017. "Three practical field normalised alternative indicator formulae for research evaluation," Journal of Informetrics, Elsevier, vol. 11(1), pages 128-151.
    2. Wang, Jue & Zhang, Liwei, 2018. "Proximal advantage in knowledge diffusion: The time dimension," Journal of Informetrics, Elsevier, vol. 12(3), pages 858-867.
    3. Osterloh, Margit & Frey, Bruno S., 2020. "How to avoid borrowed plumes in academia," Research Policy, Elsevier, vol. 49(1).
    4. Stegehuis, Clara & Litvak, Nelly & Waltman, Ludo, 2015. "Predicting the long-term citation impact of recent publications," Journal of Informetrics, Elsevier, vol. 9(3), pages 642-657.
    5. Vîiu, Gabriel-Alexandru, 2018. "The lognormal distribution explains the remarkable pattern documented by characteristic scores and scales in scientometrics," Journal of Informetrics, Elsevier, vol. 12(2), pages 401-415.
    6. 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).
    7. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    8. Martorell Cunil, Onofre & Otero González, Luis & Durán Santomil, Pablo & Mulet Forteza, Carlos, 2023. "How to accomplish a highly cited paper in the tourism, leisure and hospitality field," Journal of Business Research, Elsevier, vol. 157(C).
    9. Ling-Ling Wu & Mu-Hsuan Huang & Ching-Yi Chen, 2012. "Citation patterns of the pre-web and web-prevalent environments: The moderating effects of domain knowledge," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2182-2194, November.
    10. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    11. Thelwall, Mike, 2016. "Are the discretised lognormal and hooked power law distributions plausible for citation data?," Journal of Informetrics, Elsevier, vol. 10(2), pages 454-470.
    12. González-Albo, Borja & Bordons, María, 2011. "Articles vs. proceedings papers: Do they differ in research relevance and impact? A case study in the Library and Information Science field," Journal of Informetrics, Elsevier, vol. 5(3), pages 369-381.
    13. 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).
    14. 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.
    15. Liang, Liming & Zhong, Zhen & Rousseau, Ronald, 2015. "Uncited papers, uncited authors and uncited topics: A case study in library and information science," Journal of Informetrics, Elsevier, vol. 9(1), pages 50-58.
    16. Lachance, Christian & Larivière, Vincent, 2014. "On the citation lifecycle of papers with delayed recognition," Journal of Informetrics, Elsevier, vol. 8(4), pages 863-872.
    17. Phillips, J.C., 2015. "Phase transitions in the web of science," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 173-177.
    18. Thelwall, Mike & Sud, Pardeep, 2016. "National, disciplinary and temporal variations in the extent to which articles with more authors have more impact: Evidence from a geometric field normalised citation indicator," Journal of Informetrics, Elsevier, vol. 10(1), pages 48-61.
    19. Sangwal, Keshra, 2013. "Comparison of different mathematical functions for the analysis of citation distribution of papers of individual authors," Journal of Informetrics, Elsevier, vol. 7(1), pages 36-49.
    20. Bertoli-Barsotti, Lucio & Lando, Tommaso, 2015. "On a formula for the h-index," Journal of Informetrics, Elsevier, vol. 9(4), pages 762-776.
    21. Sangwal, Keshra, 2014. "Distributions of citations of papers of individual authors publishing in different scientific disciplines: Application of Langmuir-type function," Journal of Informetrics, Elsevier, vol. 8(4), pages 972-984.
    22. Roth, Camille & Wu, Jiang & Lozano, Sergi, 2012. "Assessing impact and quality from local dynamics of citation networks," Journal of Informetrics, Elsevier, vol. 6(1), pages 111-120.
    23. Phillips, J.C., 2013. "Self-organized criticality and color vision: A guide to water–protein landscape evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(3), pages 468-473.
    24. Sangwal, Keshra, 2013. "Citation and impact factor distributions of scientific journals published in individual countries," Journal of Informetrics, Elsevier, vol. 7(2), pages 487-504.

    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. Sangwal, Keshra, 2013. "Comparison of different mathematical functions for the analysis of citation distribution of papers of individual authors," Journal of Informetrics, Elsevier, vol. 7(1), pages 36-49.
    2. Sangwal, Keshra, 2014. "Distributions of citations of papers of individual authors publishing in different scientific disciplines: Application of Langmuir-type function," Journal of Informetrics, Elsevier, vol. 8(4), pages 972-984.
    3. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    4. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    5. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    6. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    7. Michal Brzezinski, 2015. "Power laws in citation distributions: evidence from Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 213-228, April.
    8. 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.
    9. Perc, Matjaž, 2010. "Zipf’s law and log-normal distributions in measures of scientific output across fields and institutions: 40 years of Slovenia’s research as an example," Journal of Informetrics, Elsevier, vol. 4(3), pages 358-364.
    10. Maziar Montazerian & Edgar Dutra Zanotto & Hellmut Eckert, 2019. "A new parameter for (normalized) evaluation of H-index: countries as a case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1065-1078, March.
    11. Leo Egghe, 2007. "Probabilities for encountering genius, basic, ordinary or insignificant papers based on the cumulative nth citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 167-181, January.
    12. J Mingers, 2008. "Exploring the dynamics of journal citations: Modelling with s-curves," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1013-1025, August.
    13. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 385-397, August.
    14. Thomas Heinze, 2013. "Creative accomplishments in science: definition, theoretical considerations, examples from science history, and bibliometric findings," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 927-940, June.
    15. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    16. 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.
    17. Bramoullé, Yann & Currarini, Sergio & Jackson, Matthew O. & Pin, Paolo & Rogers, Brian W., 2012. "Homophily and long-run integration in social networks," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1754-1786.
    18. S. Lehmann & A. D. Jackson, 2005. "Live and Dead Nodes," Computational and Mathematical Organization Theory, Springer, vol. 11(2), pages 161-170, July.
    19. Sylvan Katz, 2012. "Science Policy, Complex Innovation Systems and Performance Measures," SPRU Working Paper Series 198, SPRU - Science Policy Research Unit, University of Sussex Business School.
    20. Zhihui Zhang & Ying Cheng & Nian Cai Liu, 2015. "Improving the normalization effect of mean-based method from the perspective of optimization: optimization-based linear methods and their performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 587-607, January.

    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:infome:v:3:y:2009:i:4:p:296-303. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.