Soo-Kyoung Lee; Senator Jeong; Hong-Gee Kim; Young-Hee Yom

doi:10.4040/jkan.2011.41.5.623

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Original Article
A Social Network Analysis of Research Topics in Korean Nursing Science: Soo-Kyoung Lee, Senator Jeong, Hong-Gee Kim, Young-Hee Yom; Journal of Korean Academy of Nursing 2011;41(5):623-632.
DOI: https://doi.org/10.4040/jkan.2011.41.5.623
Published online: October 31, 2011

¹Researcher, Biomedical Knowledge Engineering Laboratory, Seoul National University, Seoul, Korea.

²Associate Professor, School of Dentistry, Seoul National University, Seoul, Korea.

³Professor, Department of Nursing, Chung-Ang University, Seoul, Korea.

Address reprint requests to: Yom, Young-Hee. Department of Nursing, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea. Tel: +82-2-820-5700, Fax: +82-2-824-7961, yhyom@cau.ac.kr

• Received: January 24, 2011 • Accepted: October 24, 2011

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Abstract
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REFERENCES

Abstract

Purpose
This study was done to explore the knowledge structure of Korean Nursing Science.
Methods
The main variables were key words from the research papers that were presented in the Journal of Korean Academy of Nursing and journals of the seven branches of the Korean Academy of Nursing. English titles and abstracts of the papers (n=5,936) published from 1995 through 2009 were included. Noun phrases were extracted from the corpora using an in-house program (BiKE Text Analyzer), and their co-occurrence networks were generated via a cosine similarity measure, and then the networks were analyzed and visualized using Pajek, a Social Network Analysis program.
Results
With the hub and authority measures, the most important research topics in Korean Nursing Science were identified. Newly emerging topics by three-year period units were observed as research trends.
Conclusion
This study provides a systematic overview on the knowledge structure of Korean Nursing Science. The Social Network Analysis for this study will be useful for identifying the knowledge structure in Nursing Science.
Keywords: Knowledge; Structure; Nursing; Bibliometrics; Social network analysis

This work was supported by the Korean Research Foundation Grant funded by the Korean Government (KRF-2008-562-D00035).

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Figure 1

The process of analysis of research topics in korean nursing science.

Figure 2

Topic clustering (Tf 10; n=126; cosine≥0.15; k-component1; component=9).

Figure 3

The k_th nearest neighbors analysis of 'elderly people' topic.

Table 1

Research Journals and Information Service (URL) (N=5,936)

^*Log-in required.

Table 2

Newly Emerging Research Topics in Korean Nursing Science (Top 2% of frequently occurring terms in a 3-year phase)

Figure & Data

REFERENCES

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