Korea Trade Review (무역학회지)

Korea Trade Research Association (한국무역학회)
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A Big Data Analysis on Research Keywords, Centrality, and Topics of International Trade using the Text Mining and Social Network

텍스트 마이닝과 소셜 네트워크 기법을 활용한 국제무역 키워드, 중심성과 토픽에 대한 빅데이터 분석

  • Chae-Deug Yi (Devision of International Trade, Pusan National University)
  • Received : 2022.07.30
  • Accepted : 2022.08.29
  • Published : 2022.08.30
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Abstract

This study aims to analyze international trade papers published in Korea during the past 2002-2022 years. Through this study, it is possible to understand the main subject and direction of research in Korea's international trade field. As the research mythologies, this study uses the big data analysis such as the text mining and Social Network Analysis such as frequency analysis, several centrality analysis, and topic analysis. After analyzing the empirical results, the frequency of key word is very high in trade, export, tariff, market, industry, and the performance of firm. However, there has been a tendency to include logistics, e-business, value and chain, and innovation over the time. The degree and closeness centrality analyses also show that the higher frequency key words also have been higher in the degree and closeness centrality. In contrast, the order of eigenvector centrality seems to be different from those of the degree and closeness centrality. The ego network shows the density of business, sale, exchange, and integration appears to be high in order unlike the frequency analysis. The topic analysis shows that the export, trade, tariff, logstics, innovation, industry, value, and chain seem to have high the probabilities of included in several topics.

Keywords

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