바로가기메뉴

본문 바로가기 주메뉴 바로가기

ACOMS+ 및 학술지 리포지터리 설명회

  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

logo

  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

대학의 연구 영역 분석을 통한 과학 기술 분야의 지식 구조 매핑에 관한 연구

Mapping Knowledge Structure of Science and Technology Based on University Research Domain Analysis

정보관리학회지 / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2009, v.26 no.2, pp.195-210
https://doi.org/10.3743/KOSIM.2009.26.2.195
정영미 (연세대학교)
한지연

Abstract

This study explores knowledge structures of science and technology disciplines using a cocitation analysis of journal subject categories with the publication data of a science & technology oriented university in Korea. References cited in the articles published by the faculty of the university were analyzed to produce MDS maps and network centralities. For the whole university research domain, six clusters were created including clusters of Biology related subjects, Medicine related subjects, Chemistry plus Engineering subjects, and multidisciplinary sciences plus other subjects of multidisciplinary nature. It was found that subjects of multidisciplinary nature and Biology related subjects function as central nodes in knowledge communication network in science and technology. Same analysis procedure was applied to two natural science disciplines and another two engineering disciplines to present knowledge structures of the departmental research domains.

keywords
knowledge structure, science mapping, MDS map, closeness centrality, betweenness centrality, social network analysis, 지식 구조, 과학 지도, 다차원척도 지도, 인접중앙성, 사이중앙성, 사회연결망 분석, knowledge structure, science mapping, MDS map, closeness centrality, betweenness centrality, social network analysis

참고문헌

1.

Bayer, A.E. (1990). Mapping intellectual structure of a scientific subfield through author cocitations. J. of the American Society for Information Science, 41(6), 444-452.

2.

Boyack, K.W. (2005). Mapping the backbone of science. Scientometrics, 64(3), 351-374.

3.

Bonacich, P. (1987). Power and centrality: a family of measures. American Sociological Review, 92, 1170-1182.

4.

Eom, S. Author Cocitation Analysis.

5.

Fernandez-Alles, M. (2005). Intellectual structure of human resources management research: a bibliometric analysis of the Journal Human Resource Management, 1985-2005. J. of the American Society for Information Science and Technology, 60(1), 161-175.

6.

Klavans, R. (2009). Toward a consensus map of science. J. of the Ame- rican Society for Information Science and Technology, 60(3), 455-476.

7.

이재윤. (2008). 연구자의 투고 학술지 현황에 근거한 국내 학문분야 네트워크 분석. 정보관리학회지, 25(4), 327-345.

8.

Leydesdorff, L. (2006). Co-occurrence matrices and their applications in information science: extending ACA to the Web environment. J. of the American Society for Information Science and Technology, 57(12), 1616-1628.

9.

Liu, Z. (2005). Visualizing the intellectual structure in urban studies; a journal co-citation analysis (1992-2002). Scientometrics, 62(3), 385 -402.

10.

McCain, K.W. (1990). Mapping authors in intellectual space: a technical overview. J. of the American Society for Information Science, 41(6), 433-443.

11.

Miguel, S. (2008). A new approach to institutional domain analysis: multilevel research fronts structure. Scientometrics, 74(3), 331-344.

12.

Moya-Anegéon, F.d. (2004). A new technique for building maps of large scientific domains based on the cocitation of classes and categories. Scientometrics, 61(1), 129-145.

13.

Moya-Anegéon, F.d. (2005). Domain analysis and information retrieval through the construction of heliocentric maps based on ISI-JCR category cocitation. Information Processing & Management, 41, 1520-1533.

14.

Moya-Anegéon, F.d. (2007). Visualizing the marrow of science. J. of the American Society for Information Science and Technology, 58(14), 2167-2179.

15.

Leydesdorff, L. (2007). Betweenness centrality as an indicator of the interdisciplinarity of scientific journals. J. of the American Society for Information Science and Technology, 58(9), 1303-1319.

16.

Leydesdorff, L. (2009). A global map of science based on the ISI subject categories. J. of the American Society for Information Science and Technology, 60(2), 348-362.

17.

Samoylenko, I. (2006). Visualizing the scientific world and its evolution. J. of the American Society for Information Science and Technology, 57(11), 1461-1469.

18.

Scott, J. (2000). Social Network Analysis: a Handbook:Sage Publications.

19.

Shibata, N. (2007). Topological analysis of citation networks to discover the future core articles. J. of the American Society for Information Science and Technology, 58(6), 872-882.

20.

Sugimoto, C.R. (2008). Using field cocitation analysis to assess reciprocal and shared impact of LIS/MIS fields. J. of the American Society for Information Science and Technology, 59(9), 1441-1453.

21.

Wallace, M.L. (2009). A new approach for detecting scientific specialties from cocitation networks. J. of the American Society for Information Science and Technology, 60(2), 240-246.

22.

White, H.D. (2003). Pathfinder networks and author cocitation analysis: a remapping of paradigmatic information scientists. J. of the American Society for Information Science and Technology, 54(5), 423-434.

23.

White, H.D. (1998). Visualizing a discipline: an author co-citation analysis of information science. J. of the American Society for Information Science, 49(4), 327-355.

24.

Zhao, D. (2007). Can citation analysis of web publications better detect research fronts?. J. of the American Society for Information Science and Technology, 58(9), 1285-1302.

정보관리학회지