디지털융복합연구 (Journal of Digital Convergence)

  • 제20권1호
  • /
  • Pages.1-13
  • /
  • 2022
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

텍스트마이닝을 이용한 미세먼지 관련 신문기사 분석

An Analysis of Newspaper Articles on Fine Particle Matter Using Text Mining Techniques

  • 양지연 (금오공과대학교 응용수학과)
  • Yang, Ji-Yeon (Dept. of Applied Mathematics, Kumoh National Institute of Technology)
  • 투고 : 2021.09.08
  • 심사 : 2022.01.20
  • 발행 : 2022.01.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구에서는 미세먼지에 대한 신문 기사의 시대별, 신문사별 특징을 살펴보고 있다. 이를 위하여 빅카인즈에서 1995년 이후 주요 신문사들의 관련 기사를 추출하였고 텍스트마이닝, 감성분석, 회귀분석을 활용하였다. 그 결과, 2010년 이전에는 대기오염도 측정 단어나 국내 오염원 관련 단어가 많이 등장했으나 2010년대에 들어서면서 "중국"이 큰 빈도로 나타났으며 정책적 대응, 미세먼지가 건강에 미치는 영향, 관련 제품에 대한 광고·홍보, 국내 오염원에 관한 기사까지 다양한 주제의 기사가 등장했다. 중앙일보, 한겨레, 경향신문은 상대적으로 정부의 정책이나 규제와 관련된 기사가 많은 반면, 대부분의 지역지에서는 지역 자체의 배출원 및 저감대책에 관한 기사가 많았다. 본 연구 결과는 미세먼지 관련 언론보도의 추이를 살필 수 있는 기초 자료로 활용될 수 있으리라 기대한다. 향후 포스트코로나 시대의 국내 미세먼지의 상황과 관련 기사의 트렌드를 추가적으로 비교, 검토할 수 있을 것이다.

This study aims to examine the trend and characteristics of newspaper articles concerned with fine particle matter. Newspaper articles since 1995 collected from Bigkinds were analyzed using text mining techniques, sentiment analysis and regression analysis. Air pollution measurement and domestic pollutants appeared frequently previously, but "China" became the keyword in the 2010s along with political action, the effects on the health, AD/PR, and domestic pollutants. Korea JoongAng Daily, Hankyoreh and Kyunghyang Shinmun have had more focused on political regulations whereas most regional daily newspapers on emission sources and reduction measures at the regional level. The results of this study are expected to be used as a reference for understanding the trend of newspaper articles. Future work includes further analysis and discussion of fine particle pollution condition and news reports in the post-COVID era.

키워드

과제정보

This research was supported by Kumoh National Institute of Technology(2021).

참고문헌

  1. National Institute of Environmental Research. (2006). Study on the Development of Comprehensive Assessment Techniques for Air Pollution. Republic of Korea: Ministry of Environment.
  2. J. K. Choi, et al. (2020). Harmfulness of Particulate Matter in Disease Progression. Journal of Life Science, 30(2), 191-201. DOI : 10.5352/JLS.2020.30.2.191
  3. Republic of Korea: Ministry of Environment. (2020). Special Act on the Reduction and Management of Fine Dust.
  4. Republic of Korea: Ministry of Environment. (2016). You can see it if you know it right away. Fine Dust.
  5. D. W. Dockery, et al. (1993). An association between air pollution and mortality in six US cities. New England Journal of Medicine, 329(24), 1753-1759. DOI : 10.1056/NEJM199312093292401
  6. J. M. Samet, et al. (2000). Fine particulate air pollution and mortality in 20 U.S. cities, 1987-1994. New England Journal of Medicine, 343(24), 1742-1749, DOI : 10.1056/NEJM200012143432401
  7. J. Lepeule, et al. (2012). Chronic exposure to fine particles and mortality: an extended follow-up of the Harvard Six Cities study from 1974 to 2009. Environmental Health Perspectives, 120(7), 965- 970, DOI : 10.1289/ehp.1104660
  8. D. Krewski, et al. (2009). Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Research Reports: Health Effects Institute.
  9. J. P. Myong. (2016). Health Effects of Particulate Matter. The Korean Journal of Medicine, 91(2), 106-113. DOI : 10.3904/kjm.2016.91.2.106
  10. Republic of Korea: Ministry of Environment. (2013). https://bit.ly/2VqVLUX
  11. Republic of Korea: Ministry of Culture, Sports and Tourism. (2020). Korean Policy Briefings. https://bit.ly/3jFocaJ
  12. Statistics Korea. (2019). The social indicator of South Korea. https://bit.ly/2XAZlNm
  13. National Council on Climate and Air Quality (2020). Report on the current state and solutions for fine particulate air pollution. https://bit.ly/3Al1gUw
  14. H. M. Byun, Y. J. Park & K. Yun. (2021). An Exploratory Study on the Policy for Facilitating of Health Behaviors Related to Particulate Matter: Using Topic and Semantic Network Analysis of Media Text. Journal of Korean Academy of Nursing, 51(1), 68-79. DOI : 10.4040/jkan.20213
  15. C. G. Choi, & C. M. Kim. (2016). Path Dependency and Social Amplification of Risk in Particulate Matter Air Pollution Management and its Implications. Journal of The Korean Regional Development Association, 28(5), 89-107. https://bit.ly/3bbCz1N https://doi.org/10.22885/KRDA.2016.28.5.89
  16. Y. Kim, et al. (2015). How Does Media Construct Particulate Matter Risks? : A News Frame and Source Analysis on Particulate Matter Risks. Korean Journal of Journalism & Communication Studies, 59(2), 121-154. DOI : 10.20879/kjjcs.2018.62.4.004
  17. Y. Kim, et al. (2017). A Study on the Environmental Risk Information Seeking and Processing Model about Particulate Matter: Focusing on the Moderating Effects of China Attribution, Health Symptom Experience, Perceived Information Capacity, and Relevant Channel Beliefs. Korean Journal of Communication Studies, 25(2), 5-44. DOI : 10.23875/kca.25.2.1
  18. J. W. Rhee, & S. H. Kim. (2018). News frames in the coverage of fine-dust disaster-Application of Structural Topic Modeling. Korean Journal of Journalism & Communication Studies, 62(4), 125-158. DOI : 10.20879/kjjcs.2018.62.4.004
  19. World Health Organization. (2016). Ambient air pollution: A global assessment of exposure and burden of disease. Geneva: World Health Organization. https://bit.ly/3vL0238
  20. S. Kyung, & S. H. Jeong. (2017). Adverse health effects of particulate matter. Journal of the Korean Medical Association, 60(5), 391-398. DOI : 10.5124/jkma.2017.60.5.391
  21. G. D. Thurston, et al. (2017). A joint ERS/ATS policy statement: what constitutes an adverse health effect of air pollution? An analytical framework. European Respiratory Journal, 49(1). DOI : 10.1183/13993003.00419-2016
  22. OECD (2016). The Economic Consequences of Outdoor Air Pollution. Organization for Economic Cooperation and Development. https://bit.ly/3menCCn
  23. S. E. Ahn, et al. (2017). Assessment of Human Health Effects of Air-Pollution Using Cohort DB and Estimation of Economic Costs in Korea (III). Korea Environment Institute. https://bit.ly/3EbH9JG
  24. Y. Cho, & Y. H. Sonn. (2004). Estimation of the Health Benefits for Improving Air Quality. Korea Review of Applied Economics, 6(1), 133-150. G704-001413.2004.6.1.004
  25. J. W. Min. (2019). A Survey of Citizens' Perception of Fine Particulate Matter. HRI Weekly Economic Review, 833, 1-16. https://bit.ly/3CfU0Kl
  26. S. K. Cho, J. I. Chang, & J. I. Kim. (2006). Valuing the Health Effects on Air Quality Improvement-Using Conjoint Analysis. Environmental and Resource Economics Review, 15(5), 859-884. https://bit.ly/3vJSYnz
  27. S. J. Yoon. (2009). Finding governance to prevent and mitigate social conflicts surrounding climate change response. Journal of Governance Studies, 4(2), 125-160. https://bit.ly/3nABVAS
  28. W. Chung. (2021). The Discourse Analyses of the Online News Articles and Replies on the Fine Dust Risk Issue : Based on theIssue Life Cycle Model. Korean Association for Advertising and Public Relations, 23(2), 140-183. https://bit.ly/3GpGshS https://doi.org/10.16914/kjapr.2021.23.2.140
  29. M. Kam & M. Song. (2012). A Study on Differences of Contents and Tones of Arguments among Newspapers Using Text Mining Analysis. Journal of Intelligence and Information Systems, 18(3), 53-77. DOI : 10.13088/jiis.2012.18.3.053
  30. A. Kim, et al. (2018). An Analysis of Effects of Emergency Fine Dust Reduction Measures and National Petition Using Regression Analysis and Text Mining. KIPS Transactions on Software and Data Engineering, 7(11), 427-434. DOI : 10.3745/KTSDE.2018.7.11.427
  31. S. Yoon & M. Kim. (2020). Topic Modeling on Fine Dust Issues Using LDA Analysis. Journal of Energy Engineering, 29(2), 23-29. DOI : 10.5855/ENERGY.2020.29.2.023
  32. J. H. Gu, et al. (2019). Policy Trends and Environmental Studies through Big Data. Sungkyunkwan University. bit.ly/3GpGshS
  33. BIG KINDS. Korea Press Foundation(KPF). https://www.bigkinds.or.kr
  34. AIRKOREA. Republic of Korea: Ministry of Environment. https://www.airkorea.or.kr
  35. D. Jin, et al. (2018). A Study on the Utilization of Text Mining for Climate Environmental Issues Analysis. Korea Environment Institute. https://bit.ly/3nHr4Xw
  36. T. Hardeniya & D. A. Borikar. (2016). Dictionary based approach to sentiment analysis-a review. International Journal of Advanced Engineering, Management and Science, 2(5), 317-322. https://bit.ly/3Eq1hJ0
  37. S. M. Park, et al. (2018). KNU Korean Sentiment Lexicon: Bi-LSTM-based Method for Building a Korean Sentiment Lexicon. Journal of Intelligence and Information Systems, 24(4), 219-240. DOI : 10.13088/jiis.2018.24.4.219
  38. S. Choi. (2018). EasySenti: Easy Sentiment Analysis. github.com/SukjaeChoi/easySenti
  39. National Information Society Agency. (2017). The Issue of Particulate Matter and the Application of Big Data. NEAR & Future INSIGHT. https://bit.ly/3zn8aqK