Lee Soo Kyoung, Jeong Senator, Kim Hong Gee, Yom Young Hee
Biomedical Knowledge Engineering Laboratory, Seoul National University, Seoul, Korea.
J Korean Acad Nurs. 2011 Oct;41(5):623-32. doi: 10.4040/jkan.2011.41.5.623.
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.
目的:本研究旨在探索韩国护理科学的知识结构。 方法:主要变量为在《韩国护理学会杂志》及韩国护理学会七个分会的期刊上发表的研究论文中的关键词。纳入了1995年至2009年发表的论文的英文标题和摘要(n = 5936篇)。使用内部程序(BiKE文本分析器)从语料库中提取名词短语,并通过余弦相似度度量生成它们的共现网络,然后使用社会网络分析程序Pajek对网络进行分析和可视化。 结果:通过中心性和权威性度量,确定了韩国护理科学中最重要的研究主题。观察到以三年为周期单位的新出现主题作为研究趋势。 结论:本研究提供了对韩国护理科学知识结构的系统概述。本研究的社会网络分析将有助于识别护理科学中的知识结构。
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