Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of Domestic Research Trends on Space-Based Welfare Using Text Mining

텍스트 마이닝을 활용한 공간복지 관련 국내 연구 경향 분석

  • Lee, Soo-hyun (Department of Interior Architecture & Built Environment, Yonsei University) ;
  • Byun, Gi-dong (Department of Interior Architecture & Built Environment, Yonsei University) ;
  • Ha, Mi-kyoung (Department of Interior Architecture & Built Environment, Yonsei University)
  • Received : 2023.03.27
  • Accepted : 2023.08.03
  • Published : 2023.08.30
⟨ Previous Next ⟩

Abstract

This study delves into the evolving welfare paradigm, transitioning from selective support services to comprehensive space-based universal services. To accomplish this, relevant research literature linking space and welfare was gathered and subjected to text mining analysis to discern prevalent trends. The research landscape has witnessed a shift. While earlier studies predominantly concentrated on socially disadvantaged groups, a growing number of investigations no longer target specific demographics. This reflects an evolving social consciousness wherein universal welfare is progressively being integrated into scholarly discussions. As welfare beneficiaries extend to encompass the wider local populace, there arises a need for an in depth exploration of demand-oriented spatial welfare. This entails identifying the genuine welfare requirements of local residents and providing fitting spatial solutions. Although the range of studied spaces has expanded to encompass diverse areas like residential and living infrastructure facilities, the majority of research still centers around conventional social welfare facilities. This is somewhat insufficient to mirror the swiftly changing societal expectations. In this context of the new normal era, it is imperative to consolidate research across previously segmented facilities, considering the anticipated surge in multifaceted welfare service demands. Lastly, it was observed that distinct topics within the Built Environment realm, such as CPTED, universal design, and sustainable design, have intertwined with welfare discussions. Employing text mining analysis, this study endeavors to uncover research trends more objectively and quantitatively. This study's outcomes hold academic significance by enhancing comprehension of the concept of space-based welfare. It also identifies macro research trends, contributing to a more comprehensive understanding of the subject's scope and core themes.

Keywords

Acknowledgement

본 연구는 한국연구재단 4단계 BK21 사업 Co-space 4.0: 4차 산업혁명 시대의 공간복지 혁신인재양성 교육연구단의 지원을 받아 수행되었음.

References

  1. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993-1022.
  2. Choi, H. Y. (2000). A study of data mining application in information management field. Journal of Information Science Theory and Practice, 31(3), 1-20.
  3. Choi, M. M., Park, H. K., & Lee, H. J. (2017). Exploring the possibility of space-based social work practice' based on Lefebvre's space theory - A case study on the production of differential space in permanent rental housing -. Korean Journal of Social Welfare, 69(4), 99-125. https://doi.org/10.20970/kasw.2017.69.4.004
  4. Choi, Y. J., & Park, S. S. (2002). Interplay of text mining and data mining for classifying web Contents. Korean Journal of Cognitive Science, 13(3), 33-46.
  5. Ha, H., Kim, S., & Ha, M. (2022). An analysis of domestic research trends in indoor healing environment using text mining and topic modeling. Conference Journal of the Architectural Institute of Korea, 42(2), 1-4.
  6. Hong, S. H., Im, J. H., & Lee, G. J. (2021). Regional quality of life satisfaction and life SOC service gap analysis: A case of Chungcheongnam-do. LHI Journal of Land, Housing, and Urban Affairs ,12(4), 61-79.
  7. Hwang, J., Han, Y., & Lim, H. (2023). Research trend analysis on metaverse applications in South Korea: A keyword network analysis and topic modeling approach. Journal of the Architectural Institute of Korea, 39(1), 55-65. https://doi.org/10.5659/JAIK.2023.39.1.55
  8. Jung, D. E., Jung, G. J., & Yoo, S. Y. (2021). Analyzing inequality of local living service facilities in Seoul. Journal of The Urban Design Institute of Korea, 22(2), 59-78. https://doi.org/10.38195/judik.2021.04.22.2.59
  9. Kang, I. S. (2013). Women's city and satisfaction level of local life on gender perspective: A case of Changwon city. The Journal of Human Studies, 32, 247-278.
  10. Kim, J. C., Lee, J. H., Kim, G. J., Park, S. S., & Jang, D. S. (2014). Data engineering : Time series analysis of patent keywords for forecasting emerging technology. KIPS Transactions on Software and Data Engineering, 3(9), 355-360. https://doi.org/10.3745/KTSDE.2014.3.9.355
  11. Kim, J. S. (2022). Analysis on the trend and topics of researches on french language education based on LDA topic modeling. The Journal of Learner-Centered Curriculum and Instruction, 22(13), 47-58.
  12. Kim, H. J. (2020a). Space welfare × space doctor. Architecture, 64(4), 26-29.
  13. Kim, H. M., & Shin, H. J. (2018). A study on residential satisfaction and amenity using subjective and objective indices. The Korean Journal of Local Government Studies, 22(3), 115-136.
  14. Kim, S. H., Kim, T. H., & Seo, I. H. (2022). Changes in the sports industry before and after COVID-19 using big data. The Korean Journal of physical education Management, 61(6), 271-285.
  15. Kim, S. H., Chang, N. S., & Kim, K. W. (2021). Academic trend analysis of shared economy based on text mining and network analysis. Journal of the Korean Entrepreneurship Society, 16(2), 15-34.
  16. Kim, S. K., Jo, H. J., & Kang, J. Y. (2016). The status of using text mining in academic research and analysis methods. The Journal of Information Technology and Architecture, 13(2), 317-329.
  17. Kim, S. Y. (2020b). Space is welfare. Architecture, 64(4), 15-16.
  18. Kim, T. H., & Kim, E. H. (2023). Analysis of research trends in multicultural family support centers using topic modeling (LDA). Journal of Multi-Cultural Contents Studies, 43, 177-212. https://doi.org/10.15400/mccs.2023.03.43.07
  19. Kim, Y. J. (2015). Inquiring institutional identity of social welfare center in Korea. Journal of Korean Social Welfare Administration, 17(3), 27-56.
  20. Lee, H. J., Kim, J. H., & Lee, J. S. (2022). Social big data analysis on the perception about participatory sport programs : Focusing on the changes in perception of consumers before and after COVID-19 outbreak. Korean Journal of Sport Management, 27(3), 101-123. https://doi.org/10.31308/KSSM.27.3.101
  21. Lee, J. K., Kim, H. Y., & Jun, C. M. (2015). Analysis of physical environmental factors that affect pedestrian volumes by street type. Journal of the Urban Design Institute of Korea Urban Design, 16(2), 123-140.
  22. Lee, J., Lee, J., & Lee, J. (2018). A study on perception on golf apparel using big data analysis. Korean Journal of Sports Science, 27(6), 403-417. https://doi.org/10.35159/kjss.2018.12.27.6.403
  23. Lee, S. K., & Kang, T. K. (2020). The infrastructure Service Index for citizen's life quality improvement - focused on Seoul -. Journal of the Architectural Institute of Korea, 36(11), 55-64.
  24. Lee, S. Y., & Park, J. K. (2014). A Study on Supply of Public Facilities Considering Regional Demand. Basic Research Project of the Korea Institute of Local Government Administration, 1-200.
  25. Lee, Y. B. (2020). Inclusive social welfare by the combination of ordinary daily lives with living space. Architecture, 64(4), 30-33.
  26. Lim, D., & Lee, S. (2022). Analysis of research trends in public sports facilities using big data text mining. The Korea Journal of Sport, 20(4), 269-278. https://doi.org/10.46669/kss.2022.20.4.025
  27. Lim, Y. S. (2023). Issue Analysis using topic modeling: focusing on hatred articles in national daily newspapers. Journal of the Korean Data Analysis Society, 25(1), 431-443. https://doi.org/10.37727/jkdas.2022.25.1.431
  28. Moon, H. & Song, N. K. (2020). Influence of living infrastructures on the distribution of single-person households and quality of life. Seoul Studies, 21(4), 157-175.
  29. Nam, J. H., & Jo, H. E. (2019). Minimal well-being in everyday life, Life SOC. Issue & Analysis, 1-27.
  30. Newman, D., Lau, J. H., Grieser, K., & Baldwin, T. (2010). Automatic evaluation of topic coherence. In Human language technologies: The 2010 annual conference of the North American chapter of the association for computational linguistics. 100-108.
  31. Oh, S., Yu, K., Seong, E., Kang, H., & Han, S. (2020). A Study on Enactment of Framework Act on Space Welfare. Architecture & Urban Research Institute.
  32. Park, J. H., & Oh, H. J. (2017). Comparison of topic modeling methods for analyzing research trends of archives management in Korea: focused on LDA and HDP. Journal of Korean Library and Information Science Society, 48(4), 235-258. https://doi.org/10.16981/kliss.48.4.201712.235
  33. Park, S. G., & Kang, H. W. (2018). The research features analysis of leisure and recreation based on co-authors network and topic model. Korean Journal of Physical Education, 57(2), 279-289. https://doi.org/10.23949/kjpe.2018.03.57.2.19
  34. Seoul Metropolitan Government. (2022, March 3). Seoul unveils 2040 city basic plan [Press release].
  35. Yun, H. J., Park, J. H., & Yoon, J. W. (2019). Introduction of topic modeling for extracting potential information from unstructured text data: Issue analysis on news article of dementia-related physical activity. Journal of Sport Science, 30(3), 501-512.
  36. Won, Y. K., & Kim, Y. W. (2021). Analysis of research trends in Korean English education journals using topic modeling. Journal of the Korea Contents Associations,21(4),50-59.
  37. Yoon, S. U., & Kim, M. C. (2020). Topic modeling on fine dust issues using LDA analysis. Journal of Energy Engineering, 29(2), 23-29.