State Key Laboratory of Software Development Environment, Beihang University, Beijing 10091, China.
School of Economics and Management, Beihang University, Beijing 10091, China.
Sci Total Environ. 2023 Mar 15;864:161160. doi: 10.1016/j.scitotenv.2022.161160. Epub 2022 Dec 24.
Air pollution poses a great threat to public health and social stability by influencing multiple emotions. In particular, the air quality in developing countries is deteriorating along with rapid industrialization and urbanization, and multiple emotions may change along with regulation updates and air quality trending. Monitoring changes in public emotion is crucial for environmental governance. However, limited evidence exists for long-term effects of air quality on fine-grained emotions. Traditional surveys have the drawbacks of spatial limitations and high costs of time and money. Here, we use deep learning models to identify multiple emotions of over 10 million haze-related tweets and evaluate the effect of air quality on emotional predispositions for 160 cities from 2014 to 2019 in China. We find that sadness and joy are persistently associated with air quality, while anger and disgust are not. Surprisingly, the effects on fear vanished in the last three years. Moreover, air pollution initially had a greater impact on expressed fear in cities with higher income, poorer air quality and a greater percentage of women. Through popularity ranking and dynamic topic model, we interpretively revealed that people are no longer overly panicked and their attention is shifting toward policies and sources of haze. Our findings highlight the temporal evolution in the public's emotional response and provide significant implications for equitable public policies.
空气污染通过影响多种情绪，对公众健康和社会稳定构成了巨大威胁。特别是，发展中国家的空气质量随着工业化和城市化的快速发展而恶化，随着监管更新和空气质量趋势的变化，多种情绪可能会发生变化。监测公众情绪的变化对于环境治理至关重要。然而，空气质量对细微情绪的长期影响的证据有限。传统的调查方法存在空间限制和时间、金钱成本高的缺点。在这里，我们使用深度学习模型来识别 1000 多万条与雾霾相关的推文的多种情绪，并评估 2014 年至 2019 年中国 160 个城市空气质量对情绪倾向的影响。我们发现悲伤和喜悦与空气质量始终相关，而愤怒和厌恶则不然。令人惊讶的是，恐惧的影响在过去三年中消失了。此外，空气污染最初对收入较高、空气质量较差和女性比例较大的城市的表达恐惧的影响更大。通过流行度排名和动态主题模型，我们进行了解释性分析，揭示了人们不再过度恐慌，他们的注意力正在转向雾霾的政策和来源。我们的研究结果突出了公众情绪反应的时间演变，并为公平的公共政策提供了重要启示。
