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30 years of parasitology research analysed by text mining

Published online by Cambridge University Press:  01 September 2020

John T. Ellis Open the ORCID record for John T. Ellis [Opens in a new window] ,
Bethany Ellis ,
Antonio Velez-Estevez ,
Michael P. Reichel Open the ORCID record for Michael P. Reichel [Opens in a new window]  and
Manuel J. Cobo
John T. Ellis*
Affiliation:
School of Life Sciences, University of Technology Sydney, PO Box 123, Broadway, NSW, Australia
Bethany Ellis
Affiliation:
Research School of Earth Sciences, Australian National University, Canberra, ACT, Australia
Antonio Velez-Estevez
Affiliation:
Department of Computer Science and Engineering, Universidad de Cádiz, Cadiz, Spain
Michael P. Reichel
Affiliation:
Department of Population Medicine & Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
Manuel J. Cobo
Affiliation:
Department of Computer Science and Engineering, Universidad de Cádiz, Cadiz, Spain
*
Author for correspondence: John T. Ellis, E-mail: john.ellis@uts.edu.au
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Abstract

Bibliometric methods were used to analyse the major research trends, themes and topics over the last 30 years in the parasitology discipline. The tools used were SciMAT, VOSviewer and SWIFT-Review in conjunction with the parasitology literature contained in the MEDLINE, Web of Science, Scopus and Dimensions databases. The analyses show that the major research themes are dynamic and continually changing with time, although some themes identified based on keywords such as malaria, nematode, epidemiology and phylogeny are consistently referenced over time. We note the major impact of countries like Brazil has had on the literature of parasitology research. The increase in recent times of research productivity on ‘antiparasitics’ is discussed, as well as the change in emphasis on different antiparasitic drugs and insecticides over time. In summary, innovation in parasitology is global, extensive, multidisciplinary, constantly evolving and closely aligned with the availability of technology.

Keywords

Bibliometric analysesdatabaseparasitologypublishingscience mapping analysistopic modelstrends
Type
Research Article
Information
Parasitology , Volume 147 , Issue 14 , December 2020 , pp. 1643 - 1657
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Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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