使用 BERT 和因果抽取对气候变化叙事进行索引与可视化
Indexing and Visualization of Climate Change Narratives Using BERT and Causal Extraction
AI总结：
提出结合 BERT 与因果抽取的方法，从报纸文章中抽取、量化并可视化气候变化因果叙事，揭示2018年后政策、企业、宏观经济及灾害影响等叙事演变。
摘要：
在本研究中，我们提出了一种方法，用于抽取、索引和可视化“气候变化叙事”（即关于与气候变化相关的因果事件和结果事件之间联系的故事）。我们使用两种自然语言处理方法——BERT（Bidirectional Encoder Representations from Transformers，来自 Transformer 的双向编码器表示）和因果抽取——对有关气候变化的报纸文章进行文本分析，以抽取“气候变化叙事”。该方法的新颖之处在于能够抽取并量化报纸作者所假定的因果关系。通过观察随时间抽取的气候变化叙事，我们发现，自2018年以来，越来越多的叙事表明气候变化政策讨论的发展以及气候变化相关政策的实施对企业行为、宏观经济和价格动态产生了影响。我们还观察到，近期出现了聚焦于气候变化相关政策与货币政策之间联系的叙事。此外，人们日益认识到与气候变化相关的自然灾害（例如异常天气和严重洪水）对经济活动的负面影响，而这一问题可能被视为企业和政府面临的一项新挑战。本研究的方法有望应用于广泛领域，因为它可以分析各类经济主题之间的因果关系，包括通胀预期分析或货币政策沟通策略分析。
英文摘要：
In this study, we propose a methodology to extract, index, and visualize ``climate change narratives'' (stories about the connection between causal and consequential events related to climate change). We use two natural language processing methods, BERT (Bidirectional Encoder Representations from Transformers) and causal extraction, to textually analyze newspaper articles on climate change to extract ``climate change narratives.'' The novelty of the methodology could extract and quantify the causal relationships assumed by the newspaper's writers. Looking at the extracted climate change narratives over time, we find that since 2018, an increasing number of narratives suggest the impact of the development of climate change policy discussion and the implementation of climate change-related policies on corporate behaviors, macroeconomics, and price dynamics. We also observed the recent emergence of narratives focusing on the linkages between climate change-related policies and monetary policy. Furthermore, there is a growing awareness of the negative impacts of natural disasters (e.g., abnormal weather and severe floods) related to climate change on economic activities, and this issue might be perceived as a new challenge for companies and governments. The methodology of this study is expected to be applied to a wide range of fields, as it can analyze causal relationships among various economic topics, including analysis of inflation expectation or monetary policy communication strategy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
