Effects of extreme temperatures on public sentiment in 49 Chinese cities.

The rising sentiment challenges of the metropolitan residents may be attributed to the extreme temperatures. However, nationwide real-time empirical studies that examine this claim are rare. In this research, we construct a daily extreme temperature index and sentiment metric using geotagged posts on one of China's largest social media sites, Weibo, to verify this hypothesis. We find that extreme temperatures causally decrease individuals' sentiment, and extremely low temperature may decrease more than extremely high temperature. Heterogeneity analyses reveal that individuals living in high levels of PM2.5, existing new COVID-19 diagnoses and low-disposable income cities on workdays are more vulnerable to the impact of extreme temperatures on sentiment. More importantly, the results also demonstrate that the adverse effects of extremely low temperatures on sentiment are more minor for people living in northern cities with breezes. Finally, we estimate that with a one-standard increase of extremely high (low) temperature, the sentiment decreases by approximately 0.161 (0.272) units. Employing social media to monitor public sentiment can assist policymakers in developing data-driven and evidence-based policies to alleviate the adverse impacts of extreme temperatures.