Journal of Korea Trade

Korea Trade Research Association (한국무역학회)
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Safeguarding Korean Export Trade through Social Media-Driven Risk Identification and Characterization

  • Sithipolvanichgul, Juthamon (Department of Accounting, Thammasat Business School, Thammasat University) ;
  • Abrahams, Alan S. (Department of Business Information Technology, Pamplin College of Business, Virginia Tech) ;
  • Goldberg, David M. (Department of Management Information Systems, Fowler College of Business, San Diego State University) ;
  • Zaman, Nohel (Department of Information Systems and Business Analytics, College of Business Administration, Loyola Marymount University) ;
  • Baghersad, Milad (Department of Information Technology and Operation Management, College of Business, Florida Atlantic University) ;
  • Nasri, Leila (Department of Business Information Technology, Pamplin College of Business, Virginia Tech) ;
  • Ractham, Peter (Centre of Excellence in Operations and Information Management, Thammasat Business School, Thammasat University Bangkok)
  • Received : 2020.09.10
  • Accepted : 2020.12.15
  • Published : 2020.12.31
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Abstract

Purpose - Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea's reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product risk analysis methods for social media with a specific focus on Korean-labeled products, for the purpose of safeguarding Korean export trade. Design/methodology - We employed two social media datasets containing consumer-generated product reviews. Sentiment analysis is a popular text mining technique used to quantify the type and amount of emotion that is expressed in the text. It is a useful tool for gathering customer opinions regarding products. Findings - We document and discuss the specific potential risks found in Korean-labeled products and explain their implications for safeguarding Korean export trade. Finally, we analyze the false positive matches that arise from the established dictionaries that were used for risk discovery and utilize these classification errors to suggest opportunities for the future refinement of the associated automated text analytic methods. Originality/value - Various studies have used online feedback from social media to analyze product defects. However, none of them links their findings to trade promotion and the protection of a specific country's exports. Therefore, it is important to fill this research gap, which could help to safeguard export trade in Korea.

Keywords

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