Perspect Nurs Sci.  2019 Apr;16(1):12-24. 10.16952/pns.2019.16.1.12.

Using Text Network Analysis for Analyzing Academic Papers in Nursing

• Park CS

• KMID: 2444997
• DOI: http://doi.org/10.16952/pns.2019.16.1.12

Abstract

PURPOSE
This study examined the suitability of using text network analysis (TNA) methodology for topic analysis of academic papers related to nursing.
METHODS
TNA background theories, software programs, and research processes have been described in this paper. Additionally, the research methodology that applied TNA to the topic analysis of the academic nursing papers was analyzed.
RESULTS
As background theories for the study, we explained information theory, word co-occurrence analysis, graph theory, network theory, and social network analysis. The TNA procedure was described as follows: 1) collection of academic articles, 2) text extraction, 3) preprocessing, 4) generation of word co-occurrence matrices, 5) social network analysis, and 6) interpretation and discussion.
CONCLUSION
TNA using author-keywords has several advantages. It can utilize recognized terms such as MeSH headings or terms chosen by professionals, and it saves time and effort. Additionally, the study emphasizes the necessity of developing a sophisticated research design that explores nursing research trends in a multidimensional method by applying TNA methodology.

Keyword

Text mining; Nursing methodology research; Social networking

MeSH Terms

Data Mining
Information Theory
Medical Subject Headings
Methods
Nursing Methodology Research
Nursing Research
Nursing*
Research Design
Social Networking

Figure

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  Fig. 1 The study flow of text-network analysis.

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  Fi. 2 An example of co-occurrence matrix.

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  Fig. 3A An example of word cloud.

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  Fig. 3B An example of sociogram.

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