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An Investigation on the Network Analysis Papers by Content Analysis and Bibliometric Analysis

네트워크 분석 논문의 고찰: 계량서지적 분석과 내용분석을 중심으로

  • 정은경 (이화여자대학교 사회과학대학 문헌정보학과)
  • Received : 2021.02.23
  • Accepted : 2021.03.17
  • Published : 2021.03.30

Abstract

Research in various academic fields using network analysis techniques has been conducted and grown. This study performed bibliographical analysis and content analysis on a total of 2,187 network analysis papers published in journals from 2003 to 2021. The results showed that the fields of Pedagogy, Interdisciplinary Research, Computer Science, Library and Information Science, Public Administration, and Business Administration were higher in terms of the number of research papers. From the perspective of journal, mega-journals were indicated as the most productive journals. However, when looking at the impact based on the number of citations, the strength of Public Administration, Library and Information Science, and Pedagogy is clearly revealed. The results of the analysis by authors can also confirm the higher impact of Journalism, Public Administration Science, and Library and Information Science. Of the 1,537 authors identified, very few authors are active in research, confirming the need to expand the researcher base. The results of content analysis showed that the weighted and non-directional network was the most common network type with using the research papers as a data set. Generally nodes are expressed as words and links are expressed as relationship. For network analysis, the use of KrKwic, UCINET, NetMiner, and NetDraw is the most prominent.

네트워크 분석 기법을 활용한 연구가 다양한 학문 분야에서 수행되고 있다. 본 연구는 2003년부터 2021년까지 국내 학술지에 게재된 네트워크 분석 논문 총 2,187건을 대상으로 계량서지적 분석과 내용분석을 수행하였다. 분석결과는 살펴보면, 논문 생산에 있어서 교육학, 학제간연구, 컴퓨터학, 문헌정보학, 행정학, 경영학 등의 우위를 확인할 수 있다. 학술지 단위로 보면, 메가 학술지의 강세가 나타난다. 그러나 피인용 기반의 영향력을 살펴보면, 행정학, 문헌정보학, 교육학의 영향력을 뚜렷하게 확인할 수 있다. 저자 단위로 분석한 결과 역시 언론정보학, 행정학, 문헌정보학의 우위를 확인할 수 있다. 파악된 1,537명의 저자 중에서 극소수의 저자가 활발한 연구활동을 하는 것으로 나타났으며, 이를 통해 연구자 저변 확대의 필요성도 확인할 수 있다. 내용분석의 결과를 살펴보면, 논문을 데이터셋으로 하여 가중/비방향네트워크를 형성하는 것이 가장 일반적인 네트워크 형태로 나타났다. 노드는 단어, 링크는 동시출현으로 표현되는 것이 보편적이며, 분석을 위해서는 KrKwic, UCINET, NetMiner, NetDraw 의 활용이 가장 두드러졌다.

Keywords

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