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http://dx.doi.org/10.14400/JDC.2022.20.1.001

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

Yang, Ji-Yeon (Dept. of Applied Mathematics, Kumoh National Institute of Technology)
Publication Information
Journal of Digital Convergence / v.20, no.1, 2022 , pp. 1-13 More about this Journal
Abstract
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.
Keywords
fine particle matter; text mining; newspaper; sentiment analysis; regression analysis;
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