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Highly cited papers in rheumatology: identification and conceptual analysis

Author

Listed:
  • Veronica Perez-Cabezas

    (University of Cádiz)

  • Carmen Ruiz-Molinero

    (University of Cádiz)

  • Ines Carmona-Barrientos

    (University of Cádiz)

  • Enrique Herrera-Viedma

    (University of Granada)

  • Manuel J. Cobo

    (University of Cádiz)

  • Jose A. Moral-Munoz

    (University of Cádiz
    Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), University of Cádiz)

Abstract

Rheumatology is a broad research area with an extensive background in scientific publications. Thus, the present study aims to identify the highly cited papers in Rheumatology research field, analyzing some aspects such as the documents distribution by years, journals, authors, institutions and countries. Furthermore, a conceptual evolution and a co-word analysis have been performed. In order to carry out this study, the H-Classics methodology, based on widely used H-index, has been used. A total of 317 highly cited papers have been detected from a total amount of 103.175 documents (articles and reviews) indexed in the Rheumatology category of the Web of Science database, from the period 1945–2016. As a result, it is obtained that Arthritis and Rheumatism is the journal with the highest number of documents, with more than half of detected documents. Professor Emery, from the University of Leeds (UK), and professor Felson, from the Boston University (USA), are the authors with more highly cited papers. The University of California (USA) and the University of Stanford (USA) are the main institutional contributors. USA is the leading producer, with more than half of the highly cited papers, but it is interesting to highlight the position reached by Peoples R. China, Mexico and, South Africa when an adjustment index based in the GDP per capita is applied. Osteo-arthritis and monoclonal antibody are the leader topics of this set of documents. The present study shows a useful insight into the development and evolution of the Rheumatology research field, revealing actors that have made the most significant research contribution to its development.

Suggested Citation

  • Veronica Perez-Cabezas & Carmen Ruiz-Molinero & Ines Carmona-Barrientos & Enrique Herrera-Viedma & Manuel J. Cobo & Jose A. Moral-Munoz, 2018. "Highly cited papers in rheumatology: identification and conceptual analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 555-568, July.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:1:d:10.1007_s11192-018-2712-z
    DOI: 10.1007/s11192-018-2712-z
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    References listed on IDEAS

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    1. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2012. "SciMAT: A new science mapping analysis software tool," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(8), pages 1609-1630, August.
    2. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.
    3. M. A. Martínez & M. Herrera & J. López-Gijón & E. Herrera-Viedma, 2014. "H-Classics: characterizing the concept of citation classics through H-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1971-1983, March.
    4. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
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    Cited by:

    1. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
    2. Hamdi A. Al-Jamimi & Galal M. BinMakhashen & Lutz Bornmann, 2022. "Use of bibliometrics for research evaluation in emerging markets economies: a review and discussion of bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5879-5930, October.
    3. Sepideh Fahimifar & Khadijeh Mousavi & Fatemeh Mozaffari & Marcel Ausloos, 2023. "Identification of the most important external features of highly cited scholarly papers through 3 (i.e., Ridge, Lasso, and Boruta) feature selection data mining methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3685-3712, August.
    4. María Teresa Bastanchury-López & Carmen De-Pablos-Heredero, 2022. "A Bibliometric Analysis on Smart Cities Related to Land Use," Land, MDPI, vol. 11(12), pages 1-21, November.

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