Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Unstructured Data Quantification Scheme Based on Text Mining for User Feedback Extraction

사용자 의견 추출을 위한 텍스트 마이닝 기반 비정형 데이터 정량화 방안

  • 조중흠 (홍익대학교 산업공학과) ;
  • 정용택 (홍익대학교 산업공학과) ;
  • 최성욱 (홍익대학교 산업공학과) ;
  • 옥창수 (홍익대학교 산업공학과)
  • Received : 2018.11.12
  • Accepted : 2018.12.10
  • Published : 2018.12.31
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Abstract

People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user's opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

Keywords

References

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