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Analysis of bibliometric indicators to determine citation bias

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  • Ivan Simko

    (U.S. Department of Agriculture, Agricultural Research Service, U.S. Agricultural Research Station, Salinas, CA, USA)

Abstract

Citations of research papers and citation-related indicators are frequently used factors in determining research priorities, allocating funding, and deciding appointments, promotions and tenures. The main problem with using citations for a variety of evaluations is a substantial difference in the average number of citations received by papers in different research fields and subfields. A large number of species are subjects of biological research, but the distributions of their citations have not been studied in detail. The key objective of the present work was to determine whether the choice of experimental subjects influence bias in citations. A case study was performed on papers from 108 plant species and five research fields. Funnel plot analyses and computer simulations identified species-related citation bias within all research fields. Relationships between bibliometric indicators imply that species with a fast growing number of publications in recent years (for example, new model organisms) generally have a higher average number of citations per paper than is the overall mean for the research field. In contrast, the average number of citations received by the five most prominent papers of the species was strongly correlated with the total number of published papers from laboratories working with the species. The current study indicates that despite the high frequency of cross-species citations, citations of species show a pattern similar to separate subfields. Although these analyses were performed on plant research papers, the findings have relevance for other areas of research where experimental subjects tend to form separate subfields. To reliably compare citations across subfields, a new type of bibliometric indicator is needed. In the meantime committees evaluating quality of research should take into consideration that citations of papers within a research field might be biased due to the experimental subjects used in the studies.

Suggested Citation

  • Ivan Simko, 2015. "Analysis of bibliometric indicators to determine citation bias," Palgrave Communications, Palgrave Macmillan, vol. 1(palcomms2), pages 15011-15011, June.
  • Handle: RePEc:pal:palcom:v:2015:y:2015:i:palcomms201511:p:15011-
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    Cited by:

    1. Camil Demetrescu & Irene Finocchi & Andrea Ribichini & Marco Schaerf, 2020. "On bibliometrics in academic promotions: a case study in computer science and engineering in Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2207-2228, September.
    2. Sachin S. Gunthe & Ravindra Gettu, 2022. "A new index for assessing faculty research performance in higher educational institutions of emerging economies such as India," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4959-4976, August.

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