바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

An Interdisciplinarity Identification based upon the Mapping Between Authors' Affiliations and Research Areas

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2009, v.26 no.1, pp.147-161
https://doi.org/10.3743/KOSIM.2009.26.1.147



  • Downloaded
  • Viewed

Abstract

The purpose of this study is to identify interdisciplinarity among eight research areas based upon the correlations between researchers' department affiliations and research areas. More specifically, eight research areas and their sub-areas, 153 sub-areas with researchers' department affiliations were analyzed in terms of Pearson correlation analyses. The findings demonstrated that there was interdisciplinarity between Social Science and Multiple Science Areas, Social Science and Medical & Pharmaceutical Area, Natural Science and Medical & Pharmaceutical Area, and Medical & Pharmaceutical Area and Agricultural Science.

keywords
학제성, 소속 학과, 연구영역, interdisciplinarity, affiliation, research area, interdisciplinarity, affiliation, research area

Reference

1.

민기은. (2006). 사회과학 분야의 학제성에 관한 계량정보학적 연구 (121-126). 제13회 한국정보관리학회 학술대회 논문집. 한국정보관리학회.

2.

이재윤. (2006). 연구자 소속과 표제어 분석을 통한 국내 인지과학 분야의 학제적 구조 파악 (127-134). 제13회 한국정보관리학회 학술대회 논문집.

3.

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

4.

정호연. (2007). 학술지 인용과 웹 링크 분석을 통한 과학기술분야의 학제성 비교 연구. 정보관리학회지, 24(3), 179-200.

5.

Chen, C. R. (2007). Author affiliation index, finance journal ranking, and the pattern of authorshop. Journal of Corporate Finance, 13, 1008-1026.

6.

Cronin, B. (2008). Appliying the Author affiliation index to Library and Information Science journals. Journal of the American Society for Information Science and Technology, 59(11), 1861-1865.

7.

Leydesdorff, L. (2008). Dynam- ic animations of journal maps: Indi-cators of structural changes and inter-disciplinary developments. Journal of the American Society for Information Science and Technology, 59(11), 1810-1818.

8.

Lui, Z. (2005). . Journal of Infor- mation Science, 31(4), 308-316.

9.

Morillo, F. (2001). An approach to interdisciplinarity through biblometric indicators. Scientometrics, 51(1), 203-222.

10.

Porter, A. L. (2007). Measuring researcher interdisciplinarity. Scientometrics, 72(1), 117-147.

11.

Qin, J. (1997). Types and levels of collaboration in interdisciplinary research in the sciences. Journal of the American Society for Information Science, 48(10), 893-916.

12.

Rinia, E. J. (2002). Impact measures of interdisciplinary research in Physics. Scientometrics, 53(2), 241-248.

13.

Schunn, C. D. (1998). The growth of multidisciplinarity in the Cognitive Science society. Cognitive Science, 22(1), 107-130.

14.

Szostak, R. (2008). Classification, interdiscipli- narity, and the study of science. Jour-nal of Document, 64(3), 319-332.

15.

Tijssen, R. J. W. (1992). A quantitative assess- ment of interdisciplinary structures in science and technology: co-classification analysis. Research Policy, 21, 27-44.

Journal of the Korean Society for Information Management