한국정보시스템학회지:정보시스템연구 (The Journal of Information Systems)

  • 제32권3호
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  • Pages.133-150
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  • 2023
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  • 1229-8476(pISSN)
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  • 2733-8770(eISSN)
한국정보시스템학회 (Korea Association of Information Systems)
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의사결정나무를 활용한 온라인 소비자 리뷰 평가에 영향을 주는 핵심 키워드 도출 연구: 별점과 좋아요를 중심으로

Core Keywords Extraction forEvaluating Online Consumer Reviews Using a Decision Tree: Focusing on Star Ratings and Helpfulness Votes

  • 민경수 (국민대학교 경영학과 ) ;
  • 유동희 (경상국립대학교 경영정보학과 및 경영경제연구소 )
  • 투고 : 2023.08.14
  • 심사 : 2023.09.12
  • 발행 : 2023.09.30
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초록

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.

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