Korean J Occup Health Nurs.  2019 Nov;28(4):221-229. 10.5807/kjohn.2019.28.4.221.

A Study on Research Trend for Nurses' Workplace Bullying in Korea: Focusing on Semantic Network Analysis and Topic Modeling

Affiliations
  • 1Associate Professor, Department of Nursing, College of Nursing, Gachon University, Incheon, Korea.
  • 2Assistant Professor, Department of Nursing, College of Nursing and Health, Kongju National University, Gongju, Korea. superdr1@hanmail.net

Abstract

PURPOSE
The aim of this study was to identify core keywords and topic groups of workplace bullying researches in the past 10 years for better understanding research trend.
METHODS
The study was conducted in four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building co-occurrence matrix and 4) analyzing network features and clustering topic groups.
RESULTS
437 articles between 2010 and 2019 were retrieved from 5 databases (RISS, NDSL, Google scholar, DBPIA and Kyobo Scholar). Forty-one abstracts from these articles were extracted, and network analysis was conducted using semantic network module. The most important core keywords were "˜turnover', "˜intention', "˜factor', "˜program' and "˜nursing'. Four topic groups were identified from Korean databases. Major topics were "˜turnover' and "˜organization culture'.
CONCLUSION
After reviewing previous research, it has been found that turnover intention has been emphasized. Further research focused on various intervention is needed to relieve workplace bullying in nursing field.

Keyword

Semantics; Bullying; Nurses; Text mining; Network analysis

MeSH Terms

Bullying*
Data Mining
Intention
Korea*
Nursing
Semantics*
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