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KMID : 1140520200240010085
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Korean Journal of Emergency Medical Services
2020 Volume.24 No. 1 p.85 ~ p.92
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Analysis of key words published with the Korea Society of Emergency Medical Services journal using text mining
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Kwon Chan-Yang
Yang Hyun-Mo
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Abstract
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Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends.
Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization.
Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words.
Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.
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KEYWORD
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Text mining, MeSH, Word cloud
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FullTexts / Linksout information
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Listed journal information
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