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Inferring Atmospheric Particulate Matter Concentrations from Chinese Social Media Data
- Source :
- PLoS ONE, PLoS ONE, Vol 11, Iss 9, p e0161389 (2016)
- Publication Year :
- 2016
- Publisher :
- Public Library of Science (PLoS), 2016.
-
Abstract
- Although studies have increasingly linked air pollution to specific health outcomes, less well understood is how public perceptions of air quality respond to changing pollutant levels. The growing availability of air pollution measurements and the proliferation of social media provide an opportunity to gauge public discussion of air quality conditions. In this paper, we consider particulate matter (PM) measurements from four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chengdu) together with 112 million posts on Weibo (a popular Chinese microblogging system) from corresponding days in 2011-2013 to identify terms whose frequency was most correlated with PM levels. These correlations are used to construct an Air Discussion Index (ADI) for estimating daily PM based on the content of Weibo posts. In Beijing, the Chinese city with the most PM as measured by U.S. Embassy monitor stations, we found a strong correlation (R = 0.88) between the ADI and measured PM. In other Chinese cities with lower pollution levels, the correlation was weaker. Nonetheless, our results show that social media may be a useful proxy measurement for pollution, particularly when traditional measurement stations are unavailable, censored or misreported.
- Subjects :
- Atmospheric Science
010504 meteorology & atmospheric sciences
Air pollution
lcsh:Medicine
Social Sciences
010501 environmental sciences
medicine.disease_cause
01 natural sciences
Mathematical and Statistical Techniques
Sociology
Beijing
Data Mining
lcsh:Science
media_common
Air Pollutants
Multidisciplinary
Applied Mathematics
Simulation and Modeling
Social Communication
Particulates
Pollution
Chemistry
Social Networks
Physical Sciences
Engineering and Technology
Regression Analysis
Information Technology
Network Analysis
Algorithms
Statistics (Mathematics)
Research Article
Environmental Monitoring
Computer and Information Sciences
Pollutants
China
Environmental Engineering
Microblogging
media_common.quotation_subject
Twitter
Linear Regression Analysis
Research and Analysis Methods
Air Quality
Air Pollution
Environmental health
medicine
Environmental Chemistry
Humans
Social media
Statistical Methods
Air quality index
0105 earth and related environmental sciences
Pollutant
lcsh:R
Ecology and Environmental Sciences
Communications
Megacity
Atmospheric Chemistry
Earth Sciences
Environmental science
lcsh:Q
Particulate Matter
Social Media
Mathematics
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- PLOS ONE
- Accession number :
- edsair.doi.dedup.....4f018ac1bdc27c2d7593272df176d525