Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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Research Trends on Emotional Labor in Korea using text mining

텍스트마이닝을 활용한 감정노동 연구 동향 분석

  • 조경원 (고신대학교 의료경영학부) ;
  • 한나영 (고신대학교 의료경영학부)
  • Received : 2021.09.15
  • Accepted : 2021.11.21
  • Published : 2021.12.30
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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.

텍스트마이닝을 이용하여 연구동향을 파악하는 연구가 많은 분야에서 이루어지고 있으나 감정노동 분야에서는 텍스트마이닝을 사용하여 연구 동향을 파악한 연구는 없는 실정이다. 본 연구는 텍스트마이닝을 이용하여 2004년부터 2019년까지 한국연구재단의 한국학술지인용색인(KCI)에서 '감정 노동'이라는 주제어가 포함된 1,465건의 검색된 논문을 심층적으로 분석하여 감정노동 연구 동향을 파악하고자 한다. LDA분석으로 주제들을 추출하고, 토픽의 비중과 유사도를 확인하기 위해 IDM분석을 실시하였다. 이를 통해 유사도가 높은 토픽들의 의미유용성을 고려하여 토픽의 통합분석을 실시하였다. 연구토픽은 11개로 구분되며, 감정노동의 스트레스(12.2%), 감정노동과 사회적 지지(12.0%), 고객서비스 종사자의 감정노동(10.9%), 감정노동과 회복탄력성(10.2%), 감정노동전략(9.2%), 콜센터상담사의 감정노동(9.1%), 감정노동의 결과(9.0%), 감정노동과 직무소진(7.9%), 감성지능(7.1%), 예비돌봄서비스 종사자의 감정노동(6.6%), 감정노동과 조직문화(5.9%) 순의 비중으로 나타났다. 토픽모델링과 트렌드분석을 통하여 감정노동의 연구동향과 학문적 추이를 분석함으로써 감정노동 연구의 나아갈 방향을 제시하고자 하며 감정노동에 관한 실무적인 전략을 수립할 수 있기를 기대한다.

Keywords

Acknowledgement

이 논문은 2020년 고신대학교 교내연구비에 의하여 연구되었음

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