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http://dx.doi.org/10.22156/CS4SMB.2019.9.3.068

Exploration of Emotional Labor Research Trends in Korea through Keyword Network Analysis  

Lee, Namyeon (Department of IT Management, Hanshin University)
Kim, Joon-Hwan (Department of Paideia, Sungkyul University)
Mun, Hyung-Jin (Department of Information & Communication Engineering, Sungkyul University)
Publication Information
Journal of Convergence for Information Technology / v.9, no.3, 2019 , pp. 68-74 More about this Journal
Abstract
The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.
Keywords
Convergence; Emotional Labor; Research Trends; Keyword; Network Analysis; Text-Mining;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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