Wang Weihua, Du Jianguo, Shahzad Fakhar, Duan Xiangyi, Zhu Xiaowen
School of Management, Jiangsu University, Zhenjiang, China.
Front Psychol. 2022 Jul 25;13:847608. doi: 10.3389/fpsyg.2022.847608. eCollection 2022.
As one of the key subjects of multi-center governance of environmental concerns, public perception is crucial in forming and implementing environmental policy. Based on data science research theory and the original theory of public perception, this study proposes a research framework to analyze environmental policy through network text analysis. The primary contents are bidirectional encoder representation from transformers-convolution neural network (BERT-CNN) sentiment tendency analysis, word frequency characteristic analysis, and semantic network analysis. The realism of the suggested framework is demonstrated by using the waste classification policy as an example. The findings indicate a substantial relationship between perceived subject participation and policy pilot areas and that perceived subject participation is repeating. On this premise, specific recommendations are made to encourage policy implementation.
作为环境问题多中心治理的关键主题之一，公众认知在环境政策的形成和实施中至关重要。基于数据科学研究理论和公众认知的原理论，本研究提出了一个通过网络文本分析来分析环境政策的研究框架。主要内容包括双向编码器表征来自变换器-卷积神经网络（BERT-CNN）情感倾向分析、词频特征分析和语义网络分析。以垃圾分类政策为例，验证了所提框架的现实性。研究结果表明，感知主体参与度与政策试点地区之间存在显著关系，且感知主体参与度具有重复性。在此前提下，提出了鼓励政策实施的具体建议。
