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Distributions for cited articles from individual subjects and years

Author

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  • Thelwall, Mike
  • Wilson, Paul

Abstract

The citations to a set of academic articles are typically unevenly shared, with many articles attracting few citations and few attracting many. It is important to know more precisely how citations are distributed in order to help statistical analyses of citations, especially for sets of articles from a single discipline and a small range of years, as normally used for research evaluation. This article fits discrete versions of the power law, the lognormal distribution and the hooked power law to 20 different Scopus categories, using citations to articles published in 2004 and ignoring uncited articles. The results show that, despite its popularity, the power law is not a suitable model for collections of articles from a single subject and year, even for the purpose of estimating the slope of the tail of the citation data. Both the hooked power law and the lognormal distributions fit best for some subjects but neither is a universal optimal choice and parameter estimates for both seem to be unreliable. Hence only the hooked power law and discrete lognormal distributions should be considered for subject-and-year-based citation analysis in future and parameter estimates should always be interpreted cautiously.

Suggested Citation

  • Thelwall, Mike & Wilson, Paul, 2014. "Distributions for cited articles from individual subjects and years," Journal of Informetrics, Elsevier, vol. 8(4), pages 824-839.
  • Handle: RePEc:eee:infome:v:8:y:2014:i:4:p:824-839
    DOI: 10.1016/j.joi.2014.08.001
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    References listed on IDEAS

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    1. 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.
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    5. Didegah, Fereshteh & Thelwall, Mike, 2013. "Which factors help authors produce the highest impact research? Collaboration, journal and document properties," Journal of Informetrics, Elsevier, vol. 7(4), pages 861-873.
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    Citations

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    Cited by:

    1. Thelwall, Mike & Fairclough, Ruth, 2015. "The influence of time and discipline on the magnitude of correlations between citation counts and quality scores," Journal of Informetrics, Elsevier, vol. 9(3), pages 529-541.
    2. Alonso Rodríguez-Navarro & Ricardo Brito, 2019. "Probability and expected frequency of breakthroughs: basis and use of a robust method of research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 213-235, April.
    3. Antonio Perianes-Rodriguez & Javier Ruiz-Castillo, 2016. "A comparison of two ways of evaluating research units working in different scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 539-561, February.
    4. Thelwall, Mike, 2016. "Citation count distributions for large monodisciplinary journals," Journal of Informetrics, Elsevier, vol. 10(3), pages 863-874.
    5. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Double rank analysis for research assessment," Journal of Informetrics, Elsevier, vol. 12(1), pages 31-41.
    6. 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.
    7. Thelwall, Mike, 2016. "The precision of the arithmetic mean, geometric mean and percentiles for citation data: An experimental simulation modelling approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 110-123.
    8. 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.
    9. Hu, Zhigang & Tian, Wencan & Xu, Shenmeng & Zhang, Chunbo & Wang, Xianwen, 2018. "Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers," Journal of Informetrics, Elsevier, vol. 12(4), pages 1133-1145.
    10. Mike Thelwall, 2016. "Interpreting correlations between citation counts and other indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 337-347, July.
    11. Fairclough, Ruth & Thelwall, Mike, 2015. "More precise methods for national research citation impact comparisons," Journal of Informetrics, Elsevier, vol. 9(4), pages 895-906.
    12. Thelwall, Mike, 2016. "Are there too many uncited articles? Zero inflated variants of the discretised lognormal and hooked power law distributions," Journal of Informetrics, Elsevier, vol. 10(2), pages 622-633.
    13. 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.
    14. Thelwall, Mike & Fairclough, Ruth, 2017. "The accuracy of confidence intervals for field normalised indicators," Journal of Informetrics, Elsevier, vol. 11(2), pages 530-540.
    15. Thelwall, Mike & Fairclough, Ruth, 2015. "Geometric journal impact factors correcting for individual highly cited articles," Journal of Informetrics, Elsevier, vol. 9(2), pages 263-272.
    16. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2018. "Research assessment by percentile-based double rank analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 315-329.
    17. Thelwall, Mike, 2016. "The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression," Journal of Informetrics, Elsevier, vol. 10(2), pages 336-346.
    18. Guillermo Armando Ronda-Pupo & J. Sylvan Katz, 2017. "The scaling relationship between degree centrality of countries and their citation-based performance on Management Information Systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1285-1299, September.
    19. Wan Jing Low & Paul Wilson & Mike Thelwall, 2016. "Stopped sum models and proposed variants for citation data," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 369-384, May.
    20. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    21. Hernández-Escobedo, Quetzalcoatl & Perea-Moreno, Alberto-Jesús & Manzano-Agugliaro, Francisco, 2018. "Wind energy research in Mexico," Renewable Energy, Elsevier, vol. 123(C), pages 719-729.
    22. Zoller, Daniel & Doerfel, Stephan & Jäschke, Robert & Stumme, Gerd & Hotho, Andreas, 2016. "Posted, visited, exported: Altmetrics in the social tagging system BibSonomy," Journal of Informetrics, Elsevier, vol. 10(3), pages 732-749.

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