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Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations

Author

Listed:
  • Binbin Ye

    (College of Chinese Language and Culture, Jinan University, Guangzhou 510610, China)

  • Padmaja Krishnan

    (Division of Engineering, New York University Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates)

  • Shiguo Jia

    (School of Atmospheric Sciences, Sun Yat-Sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
    Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou 510275, China
    Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-Sen University, Guangzhou 510275, China)

Abstract

To understand the temporal variation, spatial distribution and factors influencing the public’s sensitivity to air pollution in China, this study collected air pollution data from 2210 air pollution monitoring sites from around China and used keyword-based filtering to identify individual messages related to air pollution and health on Sina Weibo during 2017–2021. By analyzing correlations between concentrations of air pollutants (PM 2.5 , PM 10 , CO, NO 2 , O 3 and SO 2 ) and related microblogs (air-pollution-related and health-related), it was found that the public is most sensitive to changes in PM 2.5 concentration from the perspectives of both China as a whole and individual provinces. Correlations between air pollution and related microblogs were also stronger when and where air quality was worse, and they were also affected by socioeconomic factors such as population, economic conditions and education. Based on the results of these correlation analyses, scientists can survey public concern about air pollution and related health outcomes on social media in real time across the country and the government can formulate air quality management measures that are aligned to public sensitivities.

Suggested Citation

  • Binbin Ye & Padmaja Krishnan & Shiguo Jia, 2022. "Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations," IJERPH, MDPI, vol. 19(23), pages 1-21, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16115-:d:991102
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    References listed on IDEAS

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    1. Zhu Tao & Aynne Kokas & Rui Zhang & Daniel S Cohan & Dan Wallach, 2016. "Inferring Atmospheric Particulate Matter Concentrations from Chinese Social Media Data," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-15, September.
    2. Zhang, Zhenhua & Zhang, Guoxing & Su, Bin, 2022. "The spatial impacts of air pollution and socio-economic status on public health: Empirical evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    3. Kazutoshi Sasahara & Yoshito Hirata & Masashi Toyoda & Masaru Kitsuregawa & Kazuyuki Aihara, 2013. "Quantifying Collective Attention from Tweet Stream," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-10, April.
    4. Mattia Acito & Cristina Fatigoni & Milena Villarini & Massimo Moretti, 2022. "Cytogenetic Effects in Children Exposed to Air Pollutants: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(11), pages 1-17, May.
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    1. Stefani Kulebanova & Jana Prodanova & Aleksandra Dedinec & Trifce Sandev & Desheng Wu & Ljupco Kocarev, 2024. "Media Sentiment on Air Pollution: Seasonal Trends in Relation to PM10 Levels," Sustainability, MDPI, vol. 16(15), pages 1-20, July.

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