Understanding the Research Process and Historical Trends in English for Medical Purposes Using Scientometrics and Co-Occurrence Analysis

Journal Title: Acta Facultatis Medicae Naissensis - Year 2019, Vol 36, Issue 3

Abstract

The present study used scientometrics and word co-occurrence analysis to identify the most important topics and to assess trends in English for medical purposes over time. Documents indexed in Scopus and Web of Science were used to examine various indicators such as keywords, countries, organizations, and authors. Search results were preprocessed through BibExcel to create a file for mapping, and word co-occurrence analysis was applied to evaluate the publications. Also, scientific maps, author’s network, and country contributions were depicted using VOSviewer and NetDraw. The most productive authors and countries were determined. Re-garding the trend analysis, highly frequent words were examined at six-year intervals. The findings indicated that 81 countries, 1,304 authors, and 799 organizations have contributed to the scientific mobility of this field. Keyword co-occurrence analysis indicated that topics have shifted from language-specific foci to interactive domains. These findings offer evidence-based information about the past and present trends in EMP research topics and trends, as well as its future directions, moving from linear patterns (solely related to linguistic components) towards a more interrelated pattern of issues clustering around a medical education and learning topics.

Authors and Affiliations

Nematullah Shomoossi, Mostafa Rad, Mansoureh Fiezabadi, Esmaeil Vaziri

Keywords

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  • EP ID EP663500
  • DOI 10.5937/afmnai1903236S
  • Views 130
  • Downloads 0

How To Cite

Nematullah Shomoossi, Mostafa Rad, Mansoureh Fiezabadi, Esmaeil Vaziri (2019). Understanding the Research Process and Historical Trends in English for Medical Purposes Using Scientometrics and Co-Occurrence Analysis. Acta Facultatis Medicae Naissensis, 36(3), 235-247. https://europub.co.uk/articles/-A-663500