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Citation Analysis of Journal-to-Journal Data : Deriving Clusters for Journal Classification

  • 간행물
    한국경영정보학회 정기 학술대회 바로가기
  • 권호(발행년)
    2021 한국경영정보학회 춘계통합학술대회 (2021.06) 바로가기
  • 페이지
    pp.223-223
  • 저자
    Fridolin Neuhuber, DongBack Seo
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A395393

원문정보

초록

영어
This bibliometric study is a citation analysis of journals that concern themselves with businessrelated topics. For this purpose, the journals from the following five categories from the Web of Science Subject Categories have been examined: “Business”, “Business & Finance”, “Economics”, “Management” and “Operations Research & Management Science”. The data is retrieved from the Journal Citation Reports 2019 for each journal that is part of one of the categories. The data includes information about the journals that the articles published in the specific journal in 2019 cited and which journals cited the articles in a specific journal (Cited Journal Data and Citing Journal Data). This data is combined by creating an asymmetrical 1- mode matrix of all journals. Then, the matrix is analyzed with Pajek and VOSviewer to create clusters of journals with a high inter-correlation through citations. In the following step, the journals in these clusters are analyzed for their disciplines, main topics, and compared to typical fields of study at universities (e.g. Accounting, Marketing, Finance, etc.) in order to highlight similarities and differences between the fields of studies and the clusters of journals.

저자

  • Fridolin Neuhuber [ University of Graz, Austria ]
  • DongBack Seo [ Dept. of Management Information Systems, Chungbuk National Univeristy ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국경영정보학회 정기 학술대회 [KMIS Conference]
    • 간기
      반년간
    • 수록기간
      1990~2025
    • 십진분류
      KDC 325 DDC 658