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Why most journal impact factors are false

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  • Moustafa, Khaled

    (Founder & Editor of ArabiXiv)

Abstract

The Journal Impact Factor (JIF) is a widely used metric for ranking journals based on the number of citations garnered by papers published over a specific timeframe. To assess the accuracy of JIF values, I compared citation counts for 20 of my own publications across six major bibliography databases: CrossRef, Web of Science, Google Scholar, Scopus, PubMed, and Publishing journal records. The analysis revealed noteworthy variations in citation counts, ranging from 10% to over 50% between the lowest and highest citation counts. Google Scholar records the highest citation numbers, while PubMed reported the lowest. Notably, Web of Science, whose citation data are used in JIF calculations, tend to underestimate citation counts compared to other databases. These findings raise concerns about the accuracy of JIF calculation, as currently based on Web of Science’s citation data. The real JIF values for most journals would differ from those annually reported by Clarivate's journal citation reports (JCR). These observations underscore the importance of comprehensive data collection and the necessity to include additional citation sources. Clarivate Analytics may need to consider integrating all citation sources for more accurate JIF values. Alternatively, Google Scholar could potentially develop its own journal or citation impact based on its extensive journal citation records.

Suggested Citation

  • Moustafa, Khaled, 2024. "Why most journal impact factors are false," OSF Preprints 8g67q, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:8g67q
    DOI: 10.31219/osf.io/8g67q
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    References listed on IDEAS

    as
    1. Khaled Moustafa, 2015. "Is there bias in editorial choice? Yes," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2249-2251, December.
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