[논문]텍스트마이닝을 이용한 미세먼지 관련 신문기사 분석

양지연

doi:10.14400/jdc.2022.20.1.001

텍스트마이닝을 이용한 미세먼지 관련 신문기사 분석
An Analysis of Newspaper Articles on Fine Particle Matter Using Text Mining Techniques 원문보기

디지털융복합연구 = Journal of digital convergence, v.20 no.1, 2022년, pp.1 - 13

초록
AI-Helper

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.

Abstract ▼ AI-Helper

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.

주제어

표/그림 (8)

그림 Fig. 1. Flowchart of the study
그림 Fig. 2. Air quality over the years in Korea
그림 Fig. 3. The number of newspaper articles
표 Table 1. Top 10 words excluding institutions or regions over time (in order of frequency).
그림 Fig. 4. Top 20 Words in each news category
표 Table 2. The proportions of news categories by newspaper (2015-2019)
표 Table 3. The proportions of news categories by newspaper (2020-)
표 Table 4. Regression analysis results.

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