바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

계량정보학적 분석을 통한특정 대학원의 핵심 연구분야 파악: 미국 상위 10개 문헌정보학 대학원을 대상으로

Employing Informetric Analysis to Identify Dominant Research Areas in the Top Ranking U.S. LIS Schools

정보관리학회지 / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2008, v.25 no.2, pp.143-155
https://doi.org/10.3743/KOSIM.2008.25.2.143
Hae-Young Kim (Yonsei University)
정영미 (연세대학교)
Ji-Hye Lee (Yonsei University)
  • 다운로드 수
  • 조회수

Abstract

Authoritative as well as objective information on ranking or dominant research areas of academic departments/schools in a certain discipline is essential for the graduate school applicants. In this study, we performed an informetric analysis to identify dominant research areas in the top 10 U.S. LIS schools. We used two different datasets of research productivity and research interests of the LIS faculty. The correspondence analysis method was employed to graphically display the association between research areas and the LIS schools. We found that the research productivity data collected from SSCI database generated a very informative map presenting which research areas were dominant in which LIS schools. We also found that for the two most productive subject areas in LIS over the past 10-year period, the proportion of research articles in information retrieval decreased to a great extent in the recent 5-year period, whereas that of information seeking behavior showed an almost same degree of increase.

keywords
계량정보학적 분석, 대응일치분석, 연구생산성, 연구분야, 문헌정보학대학원, informetric analysis, correspondence analysis, research productivity, research areas, LIS schools

참고문헌

1.

Adloms., D.. (2006). Scholarly productivity of U.S. LIS faculty. Library & Information Research, 28, 374-389.

2.

Anuradha, K. T.. (2007). Bibliometric indicators of Indian research collaboration patterns: A correspondence analysis. Scien- tometrics, 71(2), 179-189.

3.

Cronin, B.. (2006). Using the h-index to rank influential information scientists. J. of the American Society for Information Science and Technology, 57(9), 1275-1278.

4.

Dore, J. C.. (2001). How to analyze publication time trends by correspondence factor analysis: Analysis of publications by 48 countries in 18 disciplines over 12 years. J. of the American Society for Information Science and Technology, 52(9), 763-769.

5.

Dore, J. C.. (1992). Correspondence factor analysis of the publication patterns of 48 countries over the period 1981-1992. J. of the American Society for Information Science, 47(8), 588-602.

6.

Greenacre, M. J.. (1993). Correspondence Analysis in Practice:Academic Press.

7.

Imperial, J.. (2007). Useful- ness of Hirsch’s h-index to evaluate scientific research in Spain. Scientometrics, 71(2), 272-282.

8.

Meho, L. I.. (2005). Ranking the research productivity of library and information science faculty and schools: An evaluation of data sources and research methods. J. of the American Society for Information Science and Technology, 56(12), 1314-1331.

9.

Van Raan, A. F.. (2006). Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147chemistry research groups. Scientometrics, 67(3), 491-502.

정보관리학회지