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Korean Journal of Psychology: General

ISSN : 1229-067X

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Vol.39 No.3
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An Exploratory Analysis of Domestic ICT Workers' Dissatisfaction with their Jobs and Differences between Former and Incumbent Employees: Application of Topical Modeling

Korean Journal of Psychology: General / Korean Journal of Psychology: General, (P)1229-067X; (E)2734-1127
2020, v.39 no.3, pp.445-480
https://doi.org/10.22257/kjp.2020.9.39.3.445



& (2020). An Exploratory Analysis of Domestic ICT Workers' Dissatisfaction with their Jobs and Differences between Former and Incumbent Employees: Application of Topical Modeling. Korean Journal of Psychology: General, 39(3), 445-480, https://doi.org/10.22257/kjp.2020.9.39.3.445
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Abstract

This study applied the Topic Modeling method, one of the text mining techniques, to analyze the text describing the shortcomings(unsatisfactory factors) of the company in the corporate review of the recruitment platform and to analyze whether there are meaningful differences in text contents bettween the stayers and the leavers. Specifically, following the procedures proposed by Schmidel et al.(2019), we analyzed the texts describing the company's shortcomings by former and incumbent employees in the ICT sector in South Korea and derived 50 topics through Topic Modeling. 44 of the 50 topics judged to be most appropriate were labeded by referring to domestic and international research results on job attitude and predictors of turnover, and the highest percentage of topic among them was 'low salary'. Among the 44 topics, significant differences were identified between stayers and leavers. In addition, the extracted topics were similar to the variables that were important in the existing job satisfaction and turnover studies, but there were also new ones. Finally, the potential of text mining methods in the field of organizational psychology as a new approach was discussed.

keywords
job satisfaction, turnover, text-mining, topic modeling, employer review website, big data, 직무만족, 이직, 텍스트 마이닝, 토픽 모델링, 기업리뷰 웹사이트, 빅데이터

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