ClimateNLP：使用自然语言处理分析公众对气候变化的态度
ClimateNLP: Analyzing Public Sentiment Towards Climate Change Using Natural Language Processing
AI总结：
本文提出ClimateNLP框架，利用自然语言处理技术及微调模型ClimateBERT分析社交媒体推文，量化公众对气候变化的情感与认知，为政策制定提供数据支持。
摘要：
气候变化对人类健康的影响带来了前所未有的多样化挑战。除非实施基于确凿证据的积极措施，否则这些威胁可能会加剧并继续危及人类福祉。信息和通信技术的不断进步促进了社交媒体平台的广泛普及和使用。人们利用Twitter和Facebook等平台表达对各种主题的观点、想法和批评，包括紧迫的气候变化问题。社交媒体上气候变化相关内容的激增需要进行全面分析以获取有意义的见解。本文采用自然语言处理（NLP）技术分析气候变化话语，并量化与气候变化相关的推文的情感。我们使用ClimateBERT，这是一个专门针对气候变化领域微调的预训练模型。目标是识别个人表达的情感，并揭示有关气候变化的公众舆论模式。分析推文情感可以更深入地了解公众对这一关键全球挑战的看法、担忧和情绪。本实验的发现揭示了对公众情感以及与气候变化话语相关实体的宝贵见解。政策制定者、研究人员和组织可以利用此类分析来了解公众认知，识别有影响力的参与者，并制定明智的策略以应对气候变化挑战。
英文摘要：
Climate change's impact on human health poses unprecedented and diverse challenges. Unless proactive measures based on solid evidence are implemented, these threats will likely escalate and continue to endanger human well-being. The escalating advancements in information and communication technologies have facilitated the widespread availability and utilization of social media platforms. Individuals utilize platforms such as Twitter and Facebook to express their opinions, thoughts, and critiques on diverse subjects, encompassing the pressing issue of climate change. The proliferation of climate change-related content on social media necessitates comprehensive analysis to glean meaningful insights. This paper employs natural language processing (NLP) techniques to analyze climate change discourse and quantify the sentiment of climate change-related tweets. We use ClimateBERT, a pretrained model fine-tuned specifically for the climate change domain. The objective is to discern the sentiment individuals express and uncover patterns in public opinion concerning climate change. Analyzing tweet sentiments allows a deeper comprehension of public perceptions, concerns, and emotions about this critical global challenge. The findings from this experiment unearth valuable insights into public sentiment and the entities associated with climate change discourse. Policymakers, researchers, and organizations can leverage such analyses to understand public perceptions, identify influential actors, and devise informed strategies to address climate change challenges.
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。
