Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Sep 26;16(19):3607.
doi: 10.3390/ijerph16193607.

Social Big-Data Analysis of Particulate Matter, Health, and Society

Juyoung Song  1 , Tae Min Song  2
Affiliations

Social Big-Data Analysis of Particulate Matter, Health, and Society

Juyoung Song et al. Int J Environ Res Public Health. .

Abstract

The study collected particulate matter (PM)-related documents in Korea and classified main keywords related to particulate matter, health, and social problems using text and opinion mining. The study attempted to present a prediction model for important causes related to particulate matter by using social big-data analysis. Topics related to particulate matter were collected from online (online news sites, blogs, cafés, social network services, and bulletin boards) from 1 January 2015, to 31 May 2016, and 226,977 text documents were included in the analysis. The present study applied machine-learning analysis technique to forecast the risk of particulate matter. Emotions related to particulate matter were found to be 65.4% negative, 7.7% neutral, and 27.0% positive. Intelligent services that can detect early and prevent unknown crisis situations of particulate matter may be possible if risk factors of particulate matter are predicted through the linkage of the machine-learning prediction model.

Keywords: Particulate Matter; Social Big-Data Analysis; South Korea; health.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Random Forest Model of Cause-and-Disease Factor.
Figure 2
Figure 2
Decision-Tree Model of Cause-and-Disease Factor.
Figure 3
Figure 3
Random Forest Model of Cause-and-Disease Factor.
Figure 4
Figure 4
Particulate-Matter Cause-and-Disease Risk Multilayer Neural Network Prediction Model.
Figure 5
Figure 5
Disease Multilayer Neural Network Prediction Model for Causes of Particulate Matter.
Figure 6
Figure 6
Performance of Machine Learning for Predicting Disease Causes of Particulate Matter.
Figure 6
Figure 6
Performance of Machine Learning for Predicting Disease Causes of Particulate Matter.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. International Energy Agency World Energy Outlook Special Report 2016: Energy and Air Pollution. Paris, France. [(accessed on 1 May 2019)]; Available online: https://www.iea.org/publications/freepublications/publication/WorldEnerg....
    1. World Health Organization 7 Million Premature Deaths Annually Linked to Air Pollution. [(accessed on 15 May 2019)]; Available online: http://www.who.int/mediacentre/news/releases/2014/air-pollution/en/
    1. Gubler D.J., Reiter P., Ebi K.L., Yap W., Nasci R., Patz J.A. Climate variability and change in the United States: Potential impacts on vector-and rodent-borne diseases. Environ. Health Perspect. 2001;109:223–233. doi: 10.2307/3435012. - DOI - PMC - PubMed
    1. World Health Organization . Outdoor Air Pollution a Leading Environmental Cause of Cancer Deaths. International Agency for Research on Cancer; Lyon, France: 2013.
    1. Bae J., Iim Y.R., Gan S.Y., Lee J.T. Association between PM2.5 and Children’s Environmental Disease. Korea Environment Institute; Seoul, Korea: 2014. Policy Report.

Publication types

LinkOut - more resources