무역학회지 (Korea Trade Review)

한국무역학회 (Korea Trade Research Association)
권호 표지
DOI QR코드

DOI QR Code

한국의 중남미 지역연구 네트워크와 중심성 및 무역과 경제에 대한 토픽 변동분석

Network, Centrality, and Topic Analysis on Korea's Trade and Economy with Latin America and the Caribbean Area

  • Chae-Deug Yi (Devision of International Trade, Pusan National University)
  • 투고 : 2022.11.30
  • 심사 : 2022.12.30
  • 발행 : 2022.12.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

키워드

참고문헌

  1. Blei, D. M., A. Y. Ng and M. I. Jordan (2003), "Latent Dirichlet Allocation", Journal of machine Learning research, 3, 993-1022.
  2. Bonacich, P. (2007), "Some unique properties of eigenvector centrality," Social Networks, 29(4), 555-564. https://doi.org/10.1016/j.socnet.2007.04.002
  3. Carter, W. C. and S. L. Feld (2004), "Principles relating social regard to size and density of personal networks, with applications to stigma," Social Networks, 26(4), 323-329. https://doi.org/10.1016/j.socnet.2004.08.004
  4. Cha, Kyung-Mi (2011), "Latin American Regional Study Trend and Individual Nation Study", Cross-Cultural Studies, 22, 203-221.
  5. Choi, Kwon-Jun (2021), " A Study on the Research Trends of Latin American Literature in Korea -Centering on Expert Academic Journals", Latin America and Caribbean Studies, 40(3), 199-244. https://doi.org/10.17855/jlas.2021.8.40.3.199
  6. Freeman, L.C. (1978), "Centrality in social networks conceptual clarification", Social Networks 1, 215-239. https://doi.org/10.1016/0378-8733(78)90021-7
  7. Han, Jin-Sung and Ji-Hwan Yoon (2016), " Activation Strategies of the 20th BIFF using Social Big Data Text Mining Analysis", Journal of Tourism Sciences, 40(1), 133-145. https://doi.org/10.17086/JTS.2015.39.10.133.145
  8. Hong, Uk-Heon (2012), "Issues and Trends in Latin American Studiesin Korea", Asia Review, 2(2), 149-1609. https://doi.org/10.24987/SNUACAR.2012.12.2.2.149
  9. Im, Doo-Bin and Leem Byung-Hak (2020), "Analysis of Research Trends in Lusophone Studies in Korea using Text Mining", 39(4), Latin America and Caribbean Studies, 179-214. https://doi.org/10.17855/jlas.2020.8.39.4.179
  10. Kim, Nam-Gyu, Domg-Hoon Lee, Ho-Chang Choi, and William Xiu Shun Wong (2017), "Investigations on Techniques and Applications of Text Analytics", The Journal of Korean Institute of Communications and Information Sciences, 42(2), 471-492. https://doi.org/10.7840/kics.2017.42.2.471
  11. Kim, Seung-Nyeon and Lee Sang-Jik (2016), " On the Relationship between ODA and Economic Cooperation among Korea and Latin American Countries", 35(1), Latin America and Caribbean Studies, 40(3), 277-305.
  12. Knoke, D. and S. Yang (2008), Social Network Analysis, SAGE, Thousand Oaks.
  13. Ko, Hyun-Jeong (2021), "Analysis on the Research Topics of Supply Chain Risk Management using Text Mining", E-Trade Review, 19(3), 65-83.
  14. Ko, Min-Hwan and Yun-Mi Park (2022), "A study on future tourism in the post-COVID-19 era using text mining based on big data: Focused on LAN cable tours", International journal of Tourism and Hospitality. 36(5), 79-92.
  15. Kwahk, Kee-Young (2017), Social Network Analysis, the 2nd edition, Cheongram.
  16. Lee, Jee-Hoon and Jung-Suk Kim (2000), "A Study on the Research Trends in Int'l Trade Using Topic modeling", Korea Trade Review, 45(3), 55-69. https://doi.org/10.22659/KTRA.2020.45.3.55
  17. Lee, Sung-Jun and Yoon, Taek-Dong (2014), " The National Cultural Differences Between Korea and Brazil - A Critical Review of Five Cross-National Comparison Researches", Journal of International Area Stydies, 18(2), 27-54.
  18. Paranyushkin Dmitry (2011), Identifying the Pathways for Meaning Circulation using Text Network Analysis, Nodus Labs, 26, 1-26.
  19. Park, Jun-Suk, Chang-Sik Kim, and Kee-Young Kwahk (2016), "Investigation of Research Trend in Hotel Domain Using Text Mining and Social Network Analysis", Journal of Tourism and Leisure Research, 28(9), 209-226.
  20. Poulin, R., M. C. Boily, and B. R. Masse (2000), "Dynamical systems to define centrality in social networks", Social networks, 22(3),187-220. https://doi.org/10.1016/S0378-8733(00)00020-4
  21. Suh, Jeong-Meen (2020), Measuring Convergences and Divergences in APEC RTAs/FTAs: a text-mining approach, APEC Study Series, 20-02, KIEP.
  22. Yi, Chae-Deug (2022), "A Big Data Analysis on Research Keywords, Centrality, and Topics of InternationalTrade using the Text Mining and Social Network", Korea Trade Review, 47(4), 137-159. https://doi.org/10.22659/KTRA.2022.47.4.137