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

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KMID : 1003720190280040221
ÃÖÁ¤½Ç ( Choi Jeong-Sil ) - °¡Ãµ´ëÇб³ °£È£´ëÇÐ °£È£Çаú

±è¿µÁö ( Kim Young-Ji ) - °øÁÖ´ëÇб³ °£È£º¸°Ç´ëÇÐ °£È£Çаú

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.
KeyWords
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Semantics, Bullying, Nurses, Text mining, Network analysis
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