The number of standardized policy documents regarding climate policy and their publication frequency is significantly increasing. The documents are long and tedious for manual analysis, especially for policy experts, lawmakers, and citizens who lack access or domain expertise to utilize data analytics tools. Potential consequences of such a situation include reduced citizen governance and involvement in climate policies and an overall surge in analytics costs, rendering less accessibility for the public. In this work, we use a Latent Dirichlet Allocation-based pipeline for the automatic summarization and analysis of 10-years of national energy and climate plans (NECPs) for the period from 2021 to 2030, established by 27 Member States of the European Union. We focus on analyzing policy framing, the language used to describe specific issues, to detect essential nuances in the way governments frame their climate policies and achieve climate goals. The methods leverage topic modeling and clustering for the comparative analysis of policy documents across different countries. It allows for easier integration in potential user-friendly applications for the development of theories and processes of climate policy. This would further lead to better citizen governance and engagement over climate policies and public policy research.
翻译:关于气候政策的标准化政策文件数量及其出版频率显著增加。这些文件冗长而乏味于手工分析,特别是缺乏获取或域内专门知识利用数据分析工具的政策专家、立法者和公民。这种情况的潜在后果包括公民治理和参与气候政策的程度降低,分析成本总体激增,使公众更难获得。在这项工作中,我们使用一个基于冷淡的 Dirichlet 分配管道,自动总结和分析2021年至2030年期间由欧洲联盟27个成员国制定的国家能源和气候计划(NECPs)的10年期。我们侧重于分析政策框架,即用来描述具体问题的语言,以发现政府制定其气候政策和实现气候目标的方式中的基本差异。这些方法利用专题建模和集群,对不同国家的政策文件进行比较分析。这样可以更方便地纳入可能方便用户的应用,以发展气候政策的理论和进程。这将进一步导致更好的公民治理和参与气候政策和公共政策研究。