A Social Network Analysis of Research Topics in Korean Nursing Science

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.