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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
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.
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.
목차
Abstract
Ⅰ. 서론
Ⅱ. 국내외 FTA 추진현황
Ⅲ. 연구방법
Ⅳ. 연구결과
Ⅴ. 결론 및 시사점
References
참고문헌 (7)
참고문헌 신청
Kessler, J. S / 2017 / Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ / Proceedings of ACL 2017, System Demonstrations
임목삼 / 2018 / 리스크관리 측면에서 FTA 연구동향 분석 / 무역상무연구 78:119~143
Maaten, L / 2008 / Visualizing data using t-SNE / Journal of Machine Learning Research 9:2579~2605
Mikolov, T / 2013 / Distributed Representations of Words and Phrases and their Compositionality / Conference on Neural Information Processing Systems 26 (NIPS)
Pennington, J. / 2014 / GloVe: Global Vectors forWord Representation / Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) :1532~1543
임목삼 / 2018 / 리스크관리 측면에서 FTA 연구동향 분석 / 무역상무연구 78:119~143
Maaten, L / 2008 / Visualizing data using t-SNE / Journal of Machine Learning Research 9:2579~2605
Mikolov, T / 2013 / Distributed Representations of Words and Phrases and their Compositionality / Conference on Neural Information Processing Systems 26 (NIPS)
Pennington, J. / 2014 / GloVe: Global Vectors forWord Representation / Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) :1532~1543
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UCI(KEPA) : I410-ECN-0101-2020-324-001577843