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http://dx.doi.org/10.9723/jksiis.2021.26.6.119

Research Trends on Emotional Labor in Korea using text mining  

Cho, Kyoung-Won (고신대학교 의료경영학부)
Han, Na-Young (고신대학교 의료경영학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.26, no.6, 2021 , pp. 119-133 More about this Journal
Abstract
Research has been conducted in many fields to identify research trends using text mining, but in the field of emotional labor, no research has been conducted using text mining to identify research trends. This study uses text mining to deeply analyze 1,465 papers at the Korea Citation Index (KCI) from 2004 to 2019 containing the subject word 'emotional labor' to understand the trend of emotional labor researches. Topics were extracted by LDA analysis, and IDM analysis was performed to confirm the proportion and similarity of the topics. Through these methods, an integrated analysis of topics was conducted considering the usefulness of topics with high similarity. The research topics are divided into 11 categories in descending order: stress of emotional labor (12.2%), emotional labor and social support (12.0%), customer service workers' emotional labor (10.9%), emotional labor and resilience (10.2%), emotional labor strategy (9.2%), call center counselor's emotional labor (9.1%), results of emotional labor (9.0%), emotional labor and job exhaustion (7.9%), emotional intelligence (7.1%), preliminary care service workers' emotional labor (6.6%), emotional labor and organizational culture (5.9%). Through topic modeling and trend analysis, the research trend of emotional labor and the academic progress are analyzed to present the direction of emotional labor research, and it is expected that a practical strategy for emotional labor can be established.
Keywords
Emotional Labor; Text Mining; Topic Modeling; Trend Analysis;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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