한국건설관리학회논문집 (Korean Journal of Construction Engineering and Management)

  • 제18권6호
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  • Pages.13-25
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  • 2017
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  • 2005-6095(pISSN)
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  • 2465-9703(eISSN)
한국건설관리학회 (Korea Institute of Construction Engineering and Management)
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빅데이터 기반의 아파트 수요 트렌드 분석에 관한 연구

Trend Analysis of Apartments Demand based on Big Data

  • 투고 : 2017.06.30
  • 심사 : 2017.08.24
  • 발행 : 2017.11.30
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초록

아파트는 우리나라 전체 주택 중 상당 부분을 차지하는 중요한 거주형태이며 매년 증가하는 추세이다. 아파트는 일반 국민에게 주거용뿐만 아니라 수익 상품으로서의 가치를 지니며, 건설기업에게는 주요 상품, 정부에게는 공공 복지를 위한 중요한 수단중 하나이다. 따라서 아파트의 수요 트렌드를 이해하고 분석하는 것은 고객의 요구 가치에 대응하는 아파트 개발과 부동산 정책수립을 위해 중요한 현안이다. 본 연구의 목적은 주요 일간지의 뉴스기사를 빅데이터 소스로 설정하고 텍스트 마이닝 기법을 활용하여 아파트 수요 트렌드를 분석하고 주요 특징을 도출하는데 있다. 연구 결과, 빅데이터 분석을 통해 개발, 거래, 분양, 입지, 정책, 주거환경, 투자 수익 등 7개의 테마별로 아파트 수요 관련 17개 주요 트렌드가 도출되었다. 본 연구에서 제안된 연구방법론은 향후 건설산업 관련 연구에 빅데이터 분석을 접목시키는데 유용하게 활용될 수 있다.

Apartments are a major type of residence and their number has continuously increased. Apartments have multiple meanings in that for public they are not only for residence purpose but for investment, a major commodity for construction firms and a critical policy measure of public well-fare for the government. Therefore, it is critical to understand and analyze trends in apartments demand for pro-active actions. The objective of the study is to analyze and identify key trends in apartments demand based on big data drawn from articles of major daily newspapers. The study identifies 17 major trends from seven themes including development, trade, sale in lots, location requirements, policy, residential environment, and investment and profit. The research methods in the study can be usefully applied to further studies for various issues in relation to the construction industry.

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참고문헌

  1. Bae, J. H., Han. N. G., and Song, M. (2014). "Twitter Issue Tracking System by Topic Modeling Techniques" Journal of Intelligence and Information Systems, KIISS, 20(2), pp. 109-122. https://doi.org/10.13088/JIIS.2014.20.2.109
  2. Blei, D. (2012). "Probabilistic Topic Models" Communications of The ACM, 55(4), pp. 77-84. https://doi.org/10.1145/2133806.2133826
  3. Blei, D., Ng, A., and Jordan, M. (2003). "Latent Dirichlet Allocation" Journal of Machine Learning Research, 3, pp. 993-1022.
  4. Chang, J. (2015). "Package 'lda' Collapsed Gibbs Sampling Methods for Topic Models" R cran, (Apr. 8, 2017)
  5. DBGuide.net (2017). "Structured Data" Classification of collected data, (Feb. 22, 2017).
  6. Jeon, H. J. (2016). "KoNLP." (Mar. 20, 2017).
  7. Jeong, C. W., and Kim, J. J. (2012). "." Journal of The Korean Digital Architecture.Interior Association, KDAI, 12(2), pp. 53-60.
  8. Jeong, D. M., Kim, J. S., Kim G. N., Heo, J. U., On, B. W., and Kang, M. J. (2013). "A Proposal of a Keyword Extraction System for Detecting Social Issues" Journal of Intelligence and Information Systems, KIISS, 19(3), pp. 1-23. https://doi.org/10.13088/jiis.2013.19.3.001
  9. Jeong, Y.C. (2013). "Big Data" Seoul, Communicationbooks.
  10. Kang, M. S., and Suh, D. H. (2016). "Single-person household increases and housing market trend changes" KB Financial group INC., (Feb. 20, 2017).
  11. Kang, S. H. (2013). "Construction industry and Big Data" Korean Journal of Construction Engineering and Management, KICEM, 14(6), pp. 73-75. https://doi.org/10.6106/KJCEM.2013.14.4.073
  12. Kang, S. H., Kim, W. Y., and Yoo, W. S. (2014). "Awareness of construction companies and future direction about Big Data" CERIK, (Feb. 15, 2017).
  13. KBA (2016). "Research Institute of KBA Analysis Report" Research Institute of Korea Appraisal Board, KBA, 5.
  14. Kim, H. J., Jo, N. O., and Shin, K. S. (2015). "Text Mining-Based Emerging Trend Analysis for the Aviation Industry" Journal of Intelligence and Information Systems, KIISS, 21(1), pp. 65-82. https://doi.org/10.13088/jiis.2015.21.1.65
  15. Kim, J. E., and Kim, M. K. (2016). "Future housing trends seminar." Korea housing institute, , (Feb. 11, 2017).
  16. Lee, D. J., Yeon, J. H., Hwang, I. B., and Lee, S. G. (2010). "Kind Korean Morpheme Analtzer" Seoul National University Intelligent Data Systems Laboratory, (Mar. 20, 2017).
  17. Lee, S. J., and Kim. H. J. (2009). "Keyword Extraction from News Corpus using Modified TF-IDF" The Journal of Society for e-Business Studies, Society for e-Business Studies, 14(4), pp. 59-73.
  18. Lee, Y. J., Lee, S. H., and Lee, J. S. (2014). "KB Kookmin Card's Marketing Activities and Use of Big Data" Korea Business Review, KASBA, 18(1), pp. 145-176.
  19. Manning, C., Raghavan, P., and Schutze, H. (2009). "An introduction to information retrieval" Cambridge, Cambridge University Press.
  20. Min, K. Y., Kim, H. T., and Ji, Y. G. (2014). "A Pilot Study on Applying Text Mining Tools to Analyzing Steel Industry Trends" The Journal of Society for e-Business Studies, Society for e-Business Studies, 19(3), pp. 51-64. https://doi.org/10.7838/jsebs.2014.19.3.051
  21. NIA (2015). "A New Approach to the Future Strategy at age of Big data" IT&Future Strategy, NIA, 2015-14.
  22. Oh, J. A. (2014). "A Case Study on the Interior Design of Medium and Small Size Apartment" Research Bulletin of Package Culture Design, KICD, 38, pp. 37-56.
  23. Park, E. J., and Cho, S. Z. (2014). "KoNLPy: Korean natural language processing in Python" Journal of The 26th annual conference on Human & Cognitive Language Technology, KIISE, 26, pp. 133-136.
  24. Park, J. H. (2017). "Journalism without Journalist" Seoul, Communicationbooks.
  25. Park, J. H., and Song, M. (2013). "A Study on the Research Trends in Library & Information Science in Korea using Topic Modeling" Journal of the Korean Society for Information Management, KOSIM, 30(1), pp. 7-32. https://doi.org/10.3743/KOSIM.2013.30.1.007
  26. Park, J. Y., and Suh C. W. (2015). "Analysis of Changes in the Housing Market Using TF-IDF Weight Model" KOREA REAL ESTATE ACADEMY REVIEW, KREA, 63, pp. 46-58.
  27. Park, Y. S., Kim, M. K., Lee, H. J., and Cho, E. S. (2003). "A Trend Analysis of Consumers for the Development of Apartment Interior Design" Korean institute of interior design journal, KIID, 41, pp. 129-136.
  28. Pillkahn, U. (2008). "Trends und Szenarien als Werkzeuge zur Strategieentwicklung" Paris, Publicis Corporate Publishing.
  29. Seo, J. E., and Lee, G. S. (2012). "A Study on Expressiv e Methods and Current Status of Apartment Finishing Materials for Trend 'Nature'" Journal of the Architectural Institute of Korea Planning & Design, AIK, 28(3), pp. 103-110. https://doi.org/10.5659/JAIK_PD.2012.28.3.103
  30. Shin, D. H. (2016). "Computational journalism." Seoul, Communicationbooks.
  31. Sievert, C., and Shirley, K. (2016). "LDAvis: A method for visualizing and interpreting topics" Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces, Association for Computational Linguistics, pp. 63-70.
  32. Statistics Korea (2016). "2015 Population and Housing Census Total count result Press Release" Press release, Statistics Korea.
  33. Suh, D. H. (2017). "Housing market settlement and forecast for 2016 through The KB Real Estate Statistics" KB Financial group INC., (Feb. 20, 2017).
  34. TTA (2017). "Big data" Telecommunications word dictionary, TTA (Feb. 22, 2017).
  35. TTA (2017). "Crawling" Telecommunications word dictionary, TTA (Mar. 13, 2017).
  36. TTA (2017). "Informal data" Telecommunications word dictionary, TTA (Feb. 22, 2017).
  37. You, E. S., Choi, G. H., and Kim, S. H. (2015). "Study on Extraction of Keywords Using TF-IDF and Text Structure of Novels" Journal of the Korea society of computer and information, KSCI, 20(2), pp. 121-129. https://doi.org/10.9708/jksci.2015.20.2.121