Journal of Information Technology Applications and Management

  • 제26권3호
  • /
  • Pages.43-59
  • /
  • 2019
  • /
  • 1598-6284(pISSN)
  • /
  • 2508-1209(eISSN)
한국데이터전략학회 (Korea Data Strategy Society)
권호 표지
DOI QR코드

DOI QR Code

텍스트마이닝을 활용한 북한 지도자의 신년사 및 연설문 트렌드 연구

Discovering Meaningful Trends in the Inaugural Addresses of North Korean Leader Via Text Mining

  • 투고 : 2019.06.10
  • 심사 : 2019.06.21
  • 발행 : 2019.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korean new year addresses, one of most important and authoritative document publicly announced by North Korean government. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. We propose a procedure to find meaningful tendencies based on a combination of text mining, cluster analysis, and co-occurrence networks. To demonstrate applicability and effectiveness of the proposed procedure, we analyzed the inaugural addresses of Kim Jung Un of the North Korea from 2017 to 2019. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. We found that uncovered semantic structures of North Korean new year addresses closely follow major changes in North Korean government's positions toward their own people as well as outside audience such as USA and South Korea.

키워드

참고문헌

  1. Aggarwal, C. C. and Zhai, C., Mining text data, Springer, 2012.
  2. Chakraborty, G., Pagolu, M., and Garla, S., Text Mining and Analysis : Practical Methods, Examples, and Case Studies Using SAS, SAS Institute, 2013.
  3. Chang, J. Y., "A Study on Research Trends of Graph-Based Text Representations for Text Mining", Journal of the Korea Academia-Industrial Cooperation Society, Vol. 12, No. 8, 2013, pp. 3677-3688. https://doi.org/10.5762/KAIS.2011.12.8.3677
  4. Chen, Y. T. and Chen, M. C., "Using chisquare statistics to measure similarities for text categorization", Expert Systems with Applications, Vol. 38, 2011, pp. 3085-3090. https://doi.org/10.1016/j.eswa.2010.08.100
  5. Cho, G. H., Lim, S. Y., and Hur, S., "An Analysis of the Research Methodologies and Techniques in the Industrial Engineering Using Text Mining", Journal of the Korean Institute of Industrial Engineers, Vol. 40, No. 1, 2014, pp. 52-59. https://doi.org/10.7232/JKIIE.2014.40.1.052
  6. Cho, S. G. and Kim, S. B., "Finding Meaningful Pattern of Key Words in IIE Transactions Using Text Mining", Journal of the Korean Institute of Industrial Engineers, Vol. 38, No. 1, 2012, pp. 67-73. https://doi.org/10.7232/JKIIE.2012.38.1.067
  7. Cho, S. G., Cho, J., and Kim, S. B., "Discovering Meaningful Trends in the Inaugural Addresses of United States Presidents Via Text Mining", Journal of the Korean Institute of Industrial Engineers, Vol. 41, No. 5, 2015, pp. 453-460. https://doi.org/10.7232/JKIIE.2015.41.5.453
  8. Fan, W., Wallace, L., Rich, S., and Zhang, Z., "Tapping the power of text mining", Communications of the ACM, Vol. 49, No. 9, 2006, pp. 76-82. https://doi.org/10.1145/1151030.1151032
  9. Go, G. S., Jung, W. K., Shin, Y. G., Park, S. S., and Jang, D. S., "A Study on Development of Patent Information Retrieval Using Textmining", Journal of the Korea Academia-Industrial Cooperation Society, Vol. 12, No. 8, 2011, pp. 3677-3688. https://doi.org/10.5762/KAIS.2011.12.8.3677
  10. Hahm, Y. and Lee, S., "The Distinctiveness of Big Data Business Model in Its Components : A Comparative Analysis of Korea-Us Cosmetic Big Data Business Cases", Information Technology and Architecture, Vol. 13, No. 1, 2016, pp. 63-75.
  11. http://www.dailybizon.com/news/articleView.html?idxno=13108(Search Date : 2019. 4. 20.)
  12. https://thaeyongho.com/2019/01/02/김정은-신년사-평가-2-북한에서-신년사가-가진-의미/(Search Date : 2019. 4. 20.)
  13. Hu, X. and Liu, H., Text analytics in social media, Mining text data, Springer Link, 2012.
  14. Hung, J. L. and Zhang, K., "Examining mobile learning trends 2003-2008 : A categorical meta-trend analysis using text mining techniques", Journal of Computing in Higher Education, Vol. 24, No. 1, 2012, pp 1-17. https://doi.org/10.1007/s12528-011-9044-9
  15. Hymans, J. E. C., "Assessing North Korean Nuclear Intentions and Capacities : A New Approach", Journal of East Asian Studies, Vol. 8, 2008, pp. 259-292. https://doi.org/10.1017/S1598240800005324
  16. Judita, P., Stevenson, M., and Gaizauskas, R., "Exploring relation types for literature-based discovery", Journal of the American Medical Informatics Association, Vol. 2, 2015, pp. 987-992.
  17. Kim, H. Y., "Analysis of an Inaugural Address of Korean Presidents Based on Network", Korea Content Association, Vol. 3, No. 2, 2013, pp. 67-68. https://doi.org/10.5392/JKCA.2013.13.06.067
  18. Kim, H. Y., Kim, H. G., and Kang, B. M., "A Trend Analysis of Cultural consumption Based on Newspaper Texts", Journal of KIIS E : Software and Applications, Vol. 39, No. 3, 2012, pp. 244-251.
  19. Kim, H., "A Study on Presidential Leadership and Policy Agenda Setting Pattern : A Content Analysis of Korean Presidential Addresses", Journal of Korean Politics, Vol. 23, No. 2, 2014, pp. 77-102.
  20. Kim, J. S., Kim, M. W., and Hyun, B. H., "A Study on Analysis of Patent Information Based Biotechnology Research Trend and Promising Research Themes", The Korea Society for Innovation Management and Economics, Vol. 21, No. 2, 2013, pp. 25-56.
  21. Kim, M. and Koo, P., "A Study on Big Data Based Investment Strategy Using Internet Search Trends", Journal of the Korean Operations Research and Management Science Society, Vol. 38, No. 4, 2013, pp. 53-64. https://doi.org/10.7737/JKORMS.2013.38.4.053
  22. Kim, M., Notkin, D., Grossman, D., and Wilson, G., "Identifying and summarizing systematic code changes via rule inference", IEEE Transactions on Software Engineering, Vol 39, 2013, pp. 45-62. https://doi.org/10.1109/TSE.2012.16
  23. Kim, S., Cho, H., and Kang, J., "The Status of Using Text Mining in Academic Research and Analysis Methods", Journal of Information Technology and Architecture, Vol. 13, No. 2, 2016, pp. 317-329.
  24. Kim, Y., Kim, N., and Jeong, S., "Stock-Index Invest Model Using News Big Data Opinion Mining", Journal of Intelligence and Information Systems, Vol. 18, No. 2, 2012, pp. 143-156. https://doi.org/10.13088/JIIS.2012.18.2.143
  25. Kim, Y., Tian, Y., Jeong, Y., Jihee, R., and Myaeng, S. H., "Automatic discovery of technology trends from patent text", Proceedings of the ACM symposium on Applied Computing, 2009, pp. 1480-1487.
  26. Lee, C. and Moon, H., "Study on analysis of North Korea's news trends associated with provocations using text mining", Journal of National Defense Studies, Vol. 59, No. 4, 2016, pp. 103-124.
  27. Lee, M. and Kim, H., "Construction of Event Networks from Large News Data Using Text Mining Techniques", Journal of Intelligence Information System, Vol. 24, No. 1, 2018, pp. 183-203. https://doi.org/10.13088/jiis.2018.24.1.183
  28. Lee, Y. J., Seo, J. H., and Choi, J. T., "Fashion Trend Marketing Prediction Analysis Based on Opinion Mining Applying SNS Text Contents", The Journal of Korean Institute of Information Technology, Vol. 12, No. 12, 2014, pp. 163-170.
  29. Lim, E. T., "Five trends in presidential rhetoric : An analysis of rhetoric from George Washington to Bill Clinton", Presidential Studies Quarterly, Vol. 32, No. 2, 2002, pp. 328-348. https://doi.org/10.1111/j.0360-4918.2002.00223.x
  30. Liu, B., "Sentiment analysis and opinion mining", Synthesis Lectures on Human Language Technologies, Vol. 5, No. 1, 2012, pp. 1-167. https://doi.org/10.2200/S00416ED1V01Y201204HLT016
  31. Liu, B., "Sentiment Analysis and Subjectivity", Handbook of Natural Language processing, Vol. 2, 2010, pp. 627-666.
  32. Myung, J., Lee, D., and Lee, S., "A Korean Product Review Analysis System Using a Semi-Automatically Constructed Semantic Dictionary", Journal of KISS : Software and Applications, Vol. 35, No. 6, 2008, pp. 392-403.
  33. Narayanan, R., Liu, B., and Choudhary, A., "Sentiment Analysis of Conditional Sentences", Proceedings of the Conference on Empirical Methods in Natural Language Processing, Vol. 1, 2009, pp. 24-31.
  34. Oh, G. S. and Lee, K. H., Analysis of the Kim Jong-un Regime's South Korea Policy and Unification Discourse through Text Mining, Korea Institute for National Unification, 2016.
  35. Pai, M. Y., Chen, M. Y., Chu, H. C., and Chen, Y. M., "Development of a semanticbased content mapping mechanism for information retrieval", Expert Systems with Applications, Vol. 40, 2013, pp. 2447-2461. https://doi.org/10.1016/j.eswa.2012.10.056
  36. Park, H., Seo, W., Coh, B., Lee, J., and Yoon, J., "Technology Opportunity Discovery Based on Firms' Technologies and Products", Journal of the Korean Institute of Industrial Engineers, Vol. 40, No. 5, 2014, pp. 442-450. https://doi.org/10.7232/JKIIE.2014.40.5.442
  37. Park, J. H., Park, E., and Jo, D., "Automated Text Analysis of North Korean New Year Addresses, 1946-2015", Korean Political Science Review, Vol. 49, No. 2, 2015, pp. 27-62. https://doi.org/10.18854/kpsr.2015.49.2.002
  38. Rich, T. S., "Deciphering North Korea's Nuclear Rhetoric : An Automated Content Analysis of KCNA News", Asian Affairs, Vol. 39, 2012, pp. 73-89. https://doi.org/10.1080/00927678.2012.678128
  39. Ryu, J., Han, C., and Shin, H., "Sector Investment Strategies Using Big Data Trends", Information Technology and Architecture, Vol. 13, No. 1, 2016, pp. 111-121.