earticle

논문검색

텍스트마이닝을 이용한 한국응급구조학회지 중심단어 분석

원문정보

Analysis of key words published with the Korea Society of Emergency Medical Services journal using text mining

권찬양, 양현모

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

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.

목차

=Abstract =
Ⅰ. 서론
1. 연구의 필요성
2. 연구의 목적
Ⅱ. 연구방법
1. 연구설계
2. 연구대상
3. 자료수집 방법
4. 분석방법
Ⅲ. 연구결과
1. 한국응급구조학회지의 저자 선정 중심단어 빈도
2. 한국응급구조학회지 중심단어에 대한 MeSH 일치 정도
3. 저자 선정 중심단어 중 다빈도이면서 MeSH 불일치 단어
Ⅳ. 고찰
Ⅴ. 결론
ORCID ID
References

저자정보

  • 권찬양 Chan-Yang Kwon. 한국교통대학교 응급구조학과
  • 양현모 Hyun-Mo Yang. 한국교통대학교 응급구조학과

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 기관로그인 시 무료 이용이 가능합니다.

      • 4,000원

      0개의 논문이 장바구니에 담겼습니다.