关于中国公民环境投诉的主题情绪分析:使用堆叠BERT模型
Junling Liu1, Ruyin Long1, Hong Chen1
1School of Business, Jiangnan University, Wuxi, 214122, China; The Institute for National Security and Green Development, Jiangnan University, Wuxi, 214122, China.
Journal of environmental management
|October 30, 2024
概括
公民的环境投诉揭示了噪音,废物和辐射问题日益增加. 情绪正在从负面转变为中性,突出了关键地区需要紧急关注的污染解决方案.
科学领域:
- 环境科学 环境科学
- 数据科学数据科学数据科学
- 公共政策 公共政策
背景情况:
- 环境投诉对于公民参与监管和污染识别至关重要.
- 分析公众对环境问题的关注,可以了解监管的有效性.
研究的目的:
- 从中国电子政府平台 (2016-2022) 分析了102,782起环境投诉的主题和情绪.
- 确定环境投诉的趋势,季节性模式和区域热点.
主要方法:
- 集成机器学习模型 (堆叠-BERT) 应用于分析投诉文本.
- 对投诉量,主题,情绪,季节性和地理分布进行定量分析.
主要成果:
- 投诉量显示出"M形"的波动;噪音,废物和辐射投诉增加.
- 情绪从负面转变为中性,表明了积极的趋势;观察到显著的季节性模式.
- 负面情绪占主导地位 (70.41%),噪音,空气和辐射是关键话题;投诉区域和负面情绪热点之间存在很大的重叠.
结论:
- 噪音,废物和辐射是越来越多的环境问题.
- 情绪分析表明,公众的看法有所改善,但显著的负面情绪仍然存在.
- 特定地区 (广东,河北,山东,河南) 需要针对环境投诉解决的有针对性的干预措施.
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