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Does high impact factor successfully predict future citations? An analysis using Peirce’s measure

Author

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  • Gangan Prathap

    (CSIR National Institute for Interdisciplinary Science and Technology)

  • S. Mini

    (CSIR National Institute for Interdisciplinary Science and Technology)

  • P. Nishy

    (CSIR National Institute for Interdisciplinary Science and Technology)

Abstract

Journals are routinely evaluated by journal impact factors. However, more controversially, these same impact factors are often used to evaluate authors and groups as well. A more meaningful approach will be to use actual citation rates. Since in each journal there is a very highly skewed distribution of articles according to citation rates, there is little correlation between journal impact factor and actual citation rate of articles from individual scientists or research groups. Simply stated, journal impact factor does not successfully predict high citations in future. In this paper, we propose the use of Peirce’s measure of predictive success (Peirce in Science 4(93):453–454, 1884) to see if the use of journal impact factors to predict high citation rates is acceptable or not. It is seen that this measure is independent of Pearson’s correlation (Seglen 1997) and gives a more quantitative refinement of the Type I and Type II classification of Smith (Financ Manag 133–149, 2004). The measures are used to examine the portfolios of some active scientists. It is clear that the journal impact factor is not effective in predicting future citations of successful authors.

Suggested Citation

  • Gangan Prathap & S. Mini & P. Nishy, 2016. "Does high impact factor successfully predict future citations? An analysis using Peirce’s measure," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1043-1047, September.
    • Handle: RePEc:spr:scient:v:108:y:2016:i:3:d:10.1007_s11192-016-2034-y
    DOI: 10.1007/s11192-016-2034-y
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    References listed on IDEAS

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    1. Per O. Seglen, 1994. "Causal relationship between article citedness and journal impact," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(1), pages 1-11, January.
    2. Stanley D. Smith, 2004. "Is an Article in a Top Journal a Top Article?," Financial Management, Financial Management Association, vol. 33(4), Winter.
    3. Per O. Seglen, 1992. "The skewness of science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 628-638, October.
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    Cited by:

    1. Chris H. J. Hartgerink & Marino Van Zelst, 2018. "“As-You-Go” Instead of “After-the-Fact”: A Network Approach to Scholarly Communication and Evaluation," Publications, MDPI, vol. 6(2), pages 1-10, April.
    2. Mingyang Wang & Shijia Jiao & Kah-Hin Chai & Guangsheng Chen, 2019. "Building journal’s long-term impact: using indicators detected from the sustained active articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 261-283, October.
    3. Hans van Dijk & Marino van Zelst, 2020. "Comfortably Numb? Researchers’ Satisfaction with the Publication System and a Proposal for Radical Change," Publications, MDPI, vol. 8(1), pages 1-20, March.

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