Impacts of Air Pollution on Chinese Expressions of Happiness on Social Media

Authors

  • Tang Zixuan Foreign Studies College, Northeastern University, Shenyang 110819, China
  • Zhang Yichen Accounting Studies College, Shanghai University of Finance and Economics Zhejiang College, Jinhua 321000, China
  • Liu Juntong School of Public Administration, Jilin University, Changchun 130012, China
  • Zhao Xinyi Foreign Studies College, Northeastern University, Shenyang 110819, China
  • Li Peiwen Meishi Film Academy, Chongqing University, Chongqing 400044, China
  • Li Jingshu Tourism College, Huaqiao University, Fuzhou 35001, China

DOI:

https://doi.org/10.61603/ceas.v1i1.12

Keywords:

air quality, pollution, NLP, happiness

Abstract

Many studies have demonstrated that air quality is an important factor affecting national well-being. Is there a relationship between air pollution and people’s happiness? To explore this, more than 40,000 haze-related tweets on the Chinese largest microblog platform SinaWeibo were collected. Using daily data for 6 Chinese cities from January 1 to February 12, 2023, we applied natural language processing (NLP) to analyze theWeibo tweets and construct a daily city-level expressed happiness metric. A fixed effects model was applied to reveal the relationship between air pollution and happiness. We found that

a one standard deviation rise in the Air Quality Index corresponded to a 0.042 standard deviation fall in the happiness index on average. People in large and rich cities are more sensitive to air pollution, and people suffer more from air pollution on weekends and holidays than on workdays. This project may provide new insights into air pollution and public engagement, and help governments and related institutions to better understand the public’s needs regarding air quality.

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Published

2023-07-13

Issue

Section

Articles

How to Cite

Impacts of Air Pollution on Chinese Expressions of Happiness on Social Media. (2023). Cambridge Explorations in Arts and Sciences, 1(1). https://doi.org/10.61603/ceas.v1i1.12