무역학회지 (Korea Trade Review)

한국무역학회 (Korea Trade Research Association)
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초록데이터를 활용한 국내외 FTA 연구동향: 2000-2020

Trends in FTA Research of Domestic and International Journal using Paper Abstract Data

  • 윤희영 (숭의여자대학교 세무회계과) ;
  • 곽일엽 (중앙대학교 응용통계학과)
  • Hee-Young Yoon (Department of Tax Accounting, Soongeui Women's College) ;
  • Il-Youp Kwak (Department of Applied Statistics, Chung-Ang University)
  • 투고 : 2020.08.05
  • 심사 : 2020.10.29
  • 발행 : 2020.10.31
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초록

This study aims to provide the implications of research development by comparing domestic and international studies conducted on the subject of FTA. To this end, among the papers written during the period from 2000 to July 23, 2020, papers whose title is searched by FTA (Free Trade Agreement) were selected as research data. In the case of domestic research, 1,944 searches from the Korean Citation Index (KCI) and 970 from the Web of Science and SCOPUS were selected for international research, and the research trend was analyzed through keywords and abstracts. Frequency analysis and word embedding (Word2vec) were used to analyze the data and visualized using t-SNE and Scattertext. The results of the analysis are as follows. First, in the top 30 keywords of domestic and international research, 16 out of 30 were found to be the same. In domestic research, many studies have been conducted to analyze the outcomes or expected effects of countries that have concluded or discussed FTAs with Korea, on the other hand there are diverse range of study subjects in international research. Second, in the word embedding analysis, t-SNE was used to visually represent the research connection of the top 60 keywords. Finally, Scattertext was used to visually indicate which keywords were frequently used in studies from 2000 to 2010, and from 2011 to 2020. This study is the first to draw implications for academic development through abstract and keyword analysis by applying various text mining approaches to the FTA related research papers. Further in-depth research is needed, including collecting a variety of FTA related text data, comparing and analyzing FTA studies in different countries.

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과제정보

This work was supported by the National Research Foundation of Korea (NRF) grant funded by Ministry of Science and ICT(No. 2020R1C1C1A01013020). This paper utilizes the Korea Citation Index (KCI) DB provided by the Korea Research Foundation.

참고문헌

  1. Kessler, J. S. (2017) "Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ" Proceedings of ACL 2017, System Demonstrations, Vancouver, Canada.
  2. Lim, Mok-Sam and Mi-Soo Choi (2018), "An Analysis of Research Trend on Risk Management in FTA ", The International Commerce & Law Review, 78, 119-143. https://doi.org/10.35980/KRICAL.2018.05.78.119
  3. Maaten, L. and G. Hinton (2008) "Visualizing data using t-SNE", Journal of Machine Learning Research, 9, 2579-2605.
  4. Mikolov, T., I. Sutskever, K. Chen, G. Corrado and J. Dean (2013) "Distributed Representations of Words and Phrases and their Compositionality" Conference on Neural Information Processing Systems 26 (NIPS), Nevada, USA.
  5. Pennington, J., R. Socher, and C. D. Manning (2014) "GloVe: Global Vectors forWord Representation", Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 1532-1543, Doha, Qatar.
  6. Suh, Jeong-Min., Han, Ye-Eun and Joung-Youn Kim (2019), "Comparative Analysis of Korea's RTA using Text mining", Korean Journal of International Economic Laws, 17(3), 31-54. https://doi.org/10.46271/KJIEL.2019.11.17.3.31
  7. Yoon, Hee-Young (2015), "Review of FTA Research Trends and Recommendations for Future Research Direction", E-Trade Review, 13(3), 71-90.