Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter)

被引：46

作者：

Jiang, Wei ^{[1
]}

Wang, Yandong ^{[1
]}

Tsou, Ming-Hsiang ^{[2
]}

Fu, Xiaokang ^{[1
]}

机构：

[1] Wuhan Univ, State Key Lab Informat Engineer Surveying Mapping, Wuhan 430072, Hubei, Peoples R China

[2] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA

来源：

PLOS ONE | 2015年 / 10卷 / 10期

基金：

中国国家自然科学基金; 美国国家科学基金会;

关键词：

INFLUENZA;

D O I：

10.1371/journal.pone.0141185

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Outdoor air pollution is a serious problem in many developing countries today. This study focuses on monitoring the dynamic changes of air quality effectively in large cities by analyzing the spatiotemporal trends in geo-targeted social media messages with comprehensive big data filtering procedures. We introduce a new social media analytic framework to (1) investigate the relationship between air pollution topics posted in Sina Weibo (Chinese Twitter) and the daily Air Quality Index (AQI) published by China's Ministry of Environmental Protection; and (2) monitor the dynamics of air quality index by using social media messages. Correlation analysis was used to compare the connections between discussion trends in social media messages and the temporal changes in the AQI during 2012. We categorized relevant messages into three types, retweets, mobile app messages, and original individual messages finding that original individual messages had the highest correlation to the Air Quality Index. Based on this correlation analysis, individual messages were used to monitor the AQI in 2013. Our study indicates that the filtered social media messages are strongly correlated to the AQI and can be used to monitor the air quality dynamics to some extent.

引用

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