用动态主题模型分析气候政策话语变迁，揭示全球应对策略演进轨迹。
Temporal Analysis of Climate Policy Discourse: Insights from Dynamic Embedded Topic Modeling
- 采用动态嵌入主题模型（DETM）捕捉政策话语随时间演变的模式。
- 发现政策重点从温室气体减排转向实施、融资与国际合作等实践议题。
- 适合关注气候治理、政策演化与文本挖掘的研究者和决策者参考。
理解政策语言随时间的演变对评估全球应对复杂挑战（如气候变化）至关重要。传统的人工主题编码耗时且难以捕捉全球政策话语中复杂的关联性。本文应用动态嵌入主题模型（DETM）分析1995至2023年联合国气候变化框架公约（UNFCCC）的政策文件（排除2020年因新冠疫情推迟的COP26），该模型能有效建模主题的时间动态。结果显示，早期关注温室气体与国际协定，近年则聚焦实施、技术协作、能力建设、资金支持与全球协议。文章详细阐述了预处理、模型训练与时间词分布可视化流程。结果表明，DETM是分析全球政策话语演变的有效且可扩展工具。最后讨论了研究启示，并提出未来可拓展至其他政策领域。
原文摘要 · Abstract (English)
Understanding how policy language evolves over time is critical for assessing global responses to complex challenges such as climate change. Temporal analysis helps stakeholders, including policymakers and researchers, to evaluate past priorities, identify emerging themes, design governance strategies, and develop mitigation measures. Traditional approaches, such as manual thematic coding, are time-consuming and limited in capturing the complex, interconnected nature of global policy discourse. With the increasing relevance of unsupervised machine learning, these limitations can be addressed, particularly under high-volume, complex, and high-dimensional data conditions. In this work, we explore a novel approach that applies the dynamic embedded topic model (DETM) to analyze the evolution of global climate policy discourse. A probabilistic model designed to capture the temporal dynamics of topics over time. We collected a corpus of United Nations Framework Convention on Climate Change (UNFCCC) policy decisions from 1995 to 2023, excluding 2020 due to the postponement of COP26 as a result of the COVID-19 pandemic. The model reveals shifts from early emphases on greenhouse gases and international conventions to recent focuses on implementation, technical collaboration, capacity building, finance, and global agreements. Section 3 presents the modeling pipeline, including preprocessing, model training, and visualization of temporal word distributions. Our results show that DETM is a scalable and effective tool for analyzing the evolution of global policy discourse. Section 4 discusses the implications of these findings and we concluded with future directions and refinements to extend this approach to other policy domains.
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