, Volume 116, Issue 1, pp 555–568 | Cite as

Highly cited papers in rheumatology: identification and conceptual analysis

  • Veronica Perez-Cabezas
  • Carmen Ruiz-Molinero
  • Ines Carmona-Barrientos
  • Enrique Herrera-Viedma
  • Manuel J. Cobo
  • Jose A. Moral-Munoz


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.


h-index Highly cited papers Highly cited journals H-Classics Bibliometrics Rheumatology 



The present study is an extended version of an article (Perez-Cabezas et al. 2017) presented at the 16th International Conference on Scientometrics and Informetrics, Wuhan (China), 16–20 October 2017. The authors want to thanks the support of FEDER funds TIN2013-40658-P and TIN2016-75850-R and University of Cádiz project PR2016-067. On the other hand, they also want to thank the valuable comments received by the 16th International Conference on Scientometrics and Informetrics (ISSI2017) attendees, who have served to improve the extended version of the paper.


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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  • Veronica Perez-Cabezas
    • 1
  • Carmen Ruiz-Molinero
    • 1
  • Ines Carmona-Barrientos
    • 1
  • Enrique Herrera-Viedma
    • 2
  • Manuel J. Cobo
    • 3
  • Jose A. Moral-Munoz
    • 1
    • 4
  1. 1.Department of Nursing and PhysiotherapyUniversity of CádizCádizSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain
  3. 3.Department of Computer Science and EngineeringUniversity of CádizCádizSpain
  4. 4.Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), University of CádizCádizSpain

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