skip to main content

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)

Jiang, Wei ; Wang, Yandong ; Tsou, Ming-Hsiang ; Fu, Xiaokang Amaral, Luís A. Nunes

PloS one, 2015-10, Vol.10 (10), p.e0141185-e0141185 [Periódico revisado por pares]

United States: Public Library of Science

Texto completo disponível

Citações Citado por
  • Título:
    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)
  • Autor: Jiang, Wei ; Wang, Yandong ; Tsou, Ming-Hsiang ; Fu, Xiaokang
  • Amaral, Luís A. Nunes
  • Assuntos: Air Pollutants ; Air Pollution ; Air quality ; Air quality assessments ; Analysis ; Applications programs ; China ; Cities ; Correlation ; Correlation analysis ; Data management ; Developing countries ; Digital media ; Elections ; Environmental Monitoring ; Environmental protection ; Filtration ; Humans ; Influence ; LDCs ; Media ; Messages ; Mobile computing ; Outdoor air quality ; Pollution ; Social Media ; Social networks ; Spatio-Temporal Analysis ; Trends
  • É parte de: PloS one, 2015-10, Vol.10 (10), p.e0141185-e0141185
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Competing Interests: The authors have declared that no competing interests exist.
    Conceived and designed the experiments: YW WJ MT. Performed the experiments: WJ XF. Analyzed the data: YW WJ. Contributed reagents/materials/analysis tools: WJ MT XF. Wrote the paper: YW WJ MT.
    These authors also contributed equally to this work
  • Descrição: 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.
  • Editor: United States: Public Library of Science
  • Idioma: Inglês

Buscando em bases de dados remotas. Favor aguardar.