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초록데이터를 활용한 국내외 FTA 연구동향: 2000-2020Trends in FTA Research of Domestic and International Journal using Paper Abstract Data

Authors
윤희영곽일엽
Issue Date
2020
Publisher
한국무역학회
Keywords
Free Trade Agreement; Scattertext; Text Mining; Word Embedding
Citation
무역학회지, v.45, no.5, pp 37 - 53
Pages
17
Journal Title
무역학회지
Volume
45
Number
5
Start Page
37
End Page
53
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/63618
DOI
10.22659.KTRA.2020.45.5.37
ISSN
1226-2765
Abstract
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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