Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
권호 표지
DOI QR코드

DOI QR Code

An Analysis of the Research Trends for Urban Study using Topic Modeling

토픽모델링을 이용한 도시 분야 연구동향 분석

  • Jang, Sun-Young (Smart Cities Research Center, Korea Institute of Civil Engineering and Building Technology) ;
  • Jung, Seunghyun (Smart Cities Research Center, Korea Institute of Civil Engineering and Building Technology)
  • 장선영 (한국건설기술연구원 스마트시티연구센터) ;
  • 정승현 (한국건설기술연구원 스마트시티연구센터)
  • Received : 2020.12.15
  • Accepted : 2021.03.05
  • Published : 2021.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Research trends can be usefully used to determine the importance of research topics by period, identify insufficient research fields, and discover new fields. In this study, research trends of urban spaces, where various problems are occurring due to population concentration and urbanization, were analyzed by topic modeling. The analysis target was the abstracts of papers listed in the Korea Citation Index (KCI) published between 2002 and 2019. Topic modeling is an algorithm-based text mining technique that can discover a certain pattern in the entire content, and it is easy to cluster. In this study, the frequency of keywords, trends by year, topic derivation, cluster by topic, and trend by topic type were analyzed. Research in urban regeneration is increasing continuously, and it was analyzed as a field where detailed topics could be expanded in the future. Furthermore, urban regeneration is now becoming a regular research field. On the other hand, topics related to development/growth and energy/environment have entered a stagnation period. This study is meaningful because the correlation and trends between keywords were analyzed using topic modeling targeting all domestic urban studies.

연구동향은 시기별 연구주제에 대한 중요도 판단과 부족한 연구 분야를 파악하고 신규 분야를 발굴하는데 유용하게 활용될 수 있다. 본 연구에서는 인구집중과 도시화로 인해 다양한 문제가 발생하고 있는 도시공간을 대상으로 한 논문들을 대상으로 시기별 연구동향을 분석하였다. 이를 위해 2002년부터 2019년 사이에 게재된 한국학술지인용색인(KCI)에 등재된 논문의 초록을 대상으로 데이터마이닝 기법 중 하나인 토픽모델링 분석을 수행하였다. 토픽모델링은 전체 내용에서 일정한 패턴을 발견해낼 수 있는 알고리즘 기반의 텍스트마이닝 기법으로 방대한 문헌에서 주제를 찾아내고 군집하는데 용이하다. 본 연구에서는 키워드 빈도, 연도별 경향, 토픽 도출, 토픽별 군집, 토픽유형별 경향에 대한 분석을 실시하였다. 그 결과 먼저 도시재생 분야연구가 지속적으로 증가되고 있고 앞으로도 세부 주제가 확대될 수 있는 분야로 분석되었다. 그리고 도시재생 주제는 이제 정규 연구분야로 자리 잡고 있는 것으로 파악되었다. 반면, 개발/성장과 에너지/환경과 같은 주제는 정체기에 들어간 것으로 분석되었다. 본 연구는 국내 전체 도시분야 연구를 대상으로 데이터마이닝 기법인 토픽모델링을 이용하여 키워드 간 연관성과 경향을 함께 분석하였다는 데 의의가 있다.

Keywords

References

  1. J. W. Hur, J. S. Choo, "A critical survey on regional studies in Korea", Journal of the Korea Planning Association, 28(2), pp.107-119, 1993.
  2. K. Kim, Y. W. Nam, "Gentrification: Research trends and arguments", Journal of the Korea Planning Association, 33(5), pp.83-97, 1998.
  3. B. H. Ko, "A study on tile paradigm shift and planning issues in urban and regional planning", Journal of the Korean Urban Management Association, 13(2), pp.101-120, 2000.
  4. H. M. Bae, "Research trend on the landscape area examined through the Journal Analysis in Korea", Journal of the Korea Planning Association, 42(3), pp.179-190, 2007.
  5. Y. S. Kim, C. Y. Park, "Types and trends of indicators in the study of urban landscape planning", Journal of the Korea Planning Association, 41(5), pp.117-129, 2006.
  6. D. M. Blei, A. Y. Ng, M. I. Jordan, "Latent dirichlet allocation", Journal of machine Learning research, 3(Jan), pp. 993-1022, 2003.
  7. J. M. Park, J. H. Kim, S. J. Yun, "International Research Trends and Domestic Policymakers Discourse with regards to Urban Regeneration - Focusing on Semantic Network Analysis and Topic Modeling", Journal of the Korean Urban Management Association, 31(2), pp. 31-59, 2018. DOI : https://doi.org/10.36700/KRUMA.2018.06.31.2.31
  8. Y. M. Song, E. S. Lee, "A Relation between Policy and Research in the Korean Architecture & Urban Field based on a Keyword Network Analysis", Journal of the Urban Design Institute of Korea Urban Design, 19(6), pp. 83-92, 2018. DOI : https://doi.org/10.38195/judik.2018.12.19.6.83
  9. H. G. Sung, I. K. Park, K. H. Ji, J. Y. Kim, K. S. Jang, J. H. Kim, J. S. Ko, C. H. Jin, "The Analysis on Research Trend of Territorial and Urban Planning for Mack Joong Choi Through Text Mining: Focused on His Academic Papers", The Korea spatial planning review, pp. 3-26, 2019. DOI : https://doi.org/10.15793/kspr.2019.103..001
  10. S. Y. Lim, Y. M. Lim, J. Y. Lee, "Study on the Trends of U-City and Smart City Researches using Text Mining Technology", Journal of the korean society for geospatial information science, 22(3), pp. 87-97, 2014. DOI : https://doi.org/10.7319/kogsis.2014.22.3.087
  11. K. C. Park, C. H. Lee, "A Study on the Research Trends for Smart City using Topic Modeling", Journal of Internet Computing and Services, 20(3), pp. 119-128, 2019. DOI : http://dx.doi.org/10.7472/jksii.2019.20.3.119
  12. H. S. Park, D. H. Kim, S. J. Chang, "Research Trend Analysis on Smart City based on Structural Topic Modeling(STM)", Journal of Digital Contents Society, 20(9), pp. 1839-1846, 2019. DOI : https://doi.org/10.9728/dcs.2019.20.9.1839
  13. K. H. Jo, S. Y. Lee, "A Study on Regeneration Methods of Old Downtown Through Analyzing Recent Trends of Establishing Cultural Place Characteristics", Journal Of the Architectural Institute of Korea Planning & Design, 32(8), pp. 123-130, 2016. DOI: https://doi.org/10.5659/JAIK_PD.2016.32.8.123
  14. Y. J. Kim, M. J. Kim, "Identifying Urban Regeneration Research Trend", Journal of the Korean Institute of Interior Design, 28(5), pp. 51-59, 2019. DOI : https://doi.org/10.14774/JKIID.2019.28.5.051
  15. B. H. Jeong, J. W. Kim, "Topic Modeling of the Transition of the Sense of Place in Urban Regeneration Area: A Case Study of Daegu Bangcheon Market", Journal of Daegu Gyeongbuk Studies, 19(1), pp. 27-44, 2020. https://doi.org/10.23029/JDGS.2020.19.1.27
  16. H. K. Cho, Y. J. Jun, S. H. Ha, J. H. Choi, "Literature Review on the Research of Urban and Architectural Landscape using Eye Tracking Method", Proceedings of the KAIS Spring Conference 2015, The Korea Academia-Industrial cooperation Society, pp. 205-207, 2015.
  17. B. R. Yang, J. J. Ryu, "Analysis on The Academic Research Trend of The City Image in Korea", Journal of the Korea Landscape Council, 7(1), pp. 17-28, 2015.
  18. K. H. Byun, C. G. Yoo, J. R. Lee, E. J. Kang, "Characteristics on Literatures of Architecture and Urban Design related to Tourism", Journal of the Regional Association of Architectural Institute of Korea, 16(1), pp. 149-158, 2014.
  19. S. Y. Lee, S. E. Yoo, "Analysis of Domestic Research Trend on Remodeling - Focused on Design and Planing Research", Journal of the Korea Institute of Spatial Design, 14(2), pp. 167-178, 2019. DOI : https://doi.org/10.35216/kisd.2019.14.2.167
  20. I. S, Kang, J. W. Moon, J. C. Park, "Recent Research Trends of Artificial Intelligent Machine Learning in Architectural Field - Review of Domestic and International Journal Papers", Journal Of the Architectural Institute of Korea Structure & Construction, 33(4), pp. 63-68, 2017. DOI : https://doi.org/10.5659/JAIK_SC.2017.33.4.63
  21. J. E. Park, K. H. Lee, "An Analysis of Domestic Text Mining Research Trend in Architectural and Urban Planning", Spring Annual Conference of AIK 2019.4, Architectural Institute of Korea, 39(1), pp. 110-113, 2019.
  22. B. Johnston, C. Kruger, A. Jones (trans. K. B. Jo.), Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python, p.528, Packt Publishing Ltd (acorn publishing Co. in Korea), 2019, p. 256.
  23. J. H. Park, M. Song, "A Study on the Research Trends in Library & Information Science in Korea using Topic Modeling", Journal of the Korean society for information management, 30(1), pp. 7-32, 2013. DOI : https://doi.org/10.3743/KOSIM.2013.30.1.007
  24. D. M. Blei, "Probabilistic topic models", Communications of the ACM, 55(4), pp. 77-84, 2012. DOI: https://doi.org/10.1145/2133806.2133826
  25. Korea Citation Index, [Internet]. National Research Foundation of Korea, [cited 2020 December 14], Available From: https://www.kci.go.kr (accessed Nov. 12, 2020)