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利用深度学习来监测人们在社交媒体上对气候变化的看法
Ana Sofia Cardoso1,2,3, Catarina da Silva4,5,6, Andrea Soriano-Redondo7,8
1CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, 4485-661, Portugal. sofia.cardoso@cibio.up.pt.
Scientific reports
|April 28, 2025
概括
本研究引入了一个自然语言处理框架来分析社交媒体气候变化讨论. 它揭示了用户的感知,情绪和反应,发现大多数对气候影响的负面或中立情绪.
科学领域:
- 环境科学 环境科学
- 计算社会科学 计算社会科学
- 自然语言处理自然语言处理.
背景情况:
- 社交媒体平台是关于气候变化的公共话语的关键舞台.
- 了解公众的看法对于有效的气候变化减缓和政策制定至关重要.
- 现有的分析大规模社交媒体气候变化数据的方法有限.
研究的目的:
- 开发和验证可扩展的自然语言处理 (NLP) 框架,用于分析社交媒体用户对气候变化的感知和反应.
- 评估框架在识别气候变化相关内容和相关用户情绪,情绪和刺方面的有效性.
- 为西南欧洲的西班牙语,葡萄牙语和英语社交媒体提供关于气候变化的公共话语的见解.
主要方法:
- 基于自然语言处理 (NLP) 的可扩展方法框架的实施.
- 分析了超过1771万条西南欧洲的西班牙语,葡萄牙语和英语的X/Twitter帖子.
- 利用机器学习模型检测气候变化帖子,分类情绪,情感和刺,成功率高 (>84%用于检测,71-92%用于分类).
主要成果:
- 该NLP框架成功地确定了相关的气候变化帖子,并检测了与现实世界事件 (如野火,风暴) 相吻合的特定气候现象.
- 用户的反应主要是中立的 (超过35%) 或负面的 (超过39%),常见的情绪包括与气候影响有关的愤怒和悲伤.
- 很大一部分帖子 (几乎四分之一) 表现出刺,强调其在在线气候变化传播中的普遍使用.
结论:
- 开发的NLP框架提供了一种强大而可扩展的方法,用于监测社会媒体上公众对气候变化的看法.
- 调查结果表明,公众对气候变化影响的情绪大多是消极的或中立的,通常通过愤怒,悲伤和刺来表达.
- 这项研究为利用深度学习工具为气候政策和决策提供信息提供了基础,通过分析在线公共话语.
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