Journal of Information Technology Applications and Management

  • 제30권2호
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  • Pages.19-30
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  • 2023
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  • 1598-6284(pISSN)
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  • 2508-1209(eISSN)
한국데이터전략학회 (Korea Data Strategy Society)
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Analysis of Success Factors of Electric Scooter Sharing Service Using User Review Text Mining

  • 투고 : 2023.02.05
  • 심사 : 2023.02.24
  • 발행 : 2023.04.30
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초록

This study aims to analyze service improvement and success factors of electric scooter sharing service companies by using text mining after collecting reviews of shared electric scooter service applications among various models of sharing economy. In this study, the factors of satisfaction and dissatisfaction of service users were identified using the term frequency inverse document frequency (TF-IDF) technique, and topics for each keyword were extracted using the Latent Dirichlet Allocation (LDA) Topic Modeling technique. According to the analysis results, the main topics were entertainment, safety, service area, application complaints, use complaints, convenience, and mobility. Using the analysis results of this study, employees and researchers of electric scooter sharing service companies will be able to contribute to the improvement and success of related services.

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참고문헌

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