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Veterinary Research Trends Based on Semantic Network Analysis

  • The Journal of Transdisciplinary Studies
  • Abbr : JTS
  • 2024, 8(3), pp.263-271
  • Publisher : The Society for Transdisciplinary Studies
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Received : November 1, 2024
  • Accepted : November 26, 2024
  • Published : December 31, 2024

Roh Jae-hee 1

1광주여자대학교

Accredited

ABSTRACT

This study aimed to examine veterinary research trends by applying a semantic network analysis to the main keywords of articles. The analysis was conducted on 283 academic articles published in the Journal of Veterinary Science from 2020 to 2022, and the main words were refined and extracted from the English keywords presented in each article. When term frequency-inverse document frequency and term frequency were combined, the top 10 research keywords were canine, swine, feline, avian, and bovine for livestock species, and virus, cell, disease, fever, and analysis for non-livestock species. The results of an N-gram analysis also revealed that African swine fever and stem cells were the top research topics identified. The results of a centrality analysis showed that disease, analysis, and virus ranked highest in terms of research interest and impact for non-livestock species, whereas swine ranked highest in terms of those for livestock species. The results of a research trend analysis provided further useful information to guide future research and present directions on the topic. The results of this study are expected to provide evidence for identifying research trends in veterinary science and provide useful information for future research.

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