Nowadays social media platforms such as Twitter provide a great opportunity to understand public opinion of climate change compared to traditional survey methods. In this paper, we constructed a massive climate change Twitter dataset and conducted comprehensive analysis using machine learning. By conducting topic modeling and natural language processing, we show the relationship between the number of tweets about climate change and major climate events; the common topics people discuss climate change; and the trend of sentiment. Our dataset was published on Kaggle (\url{https://www.kaggle.com/leonshangguan/climate-change-tweets-ids-until-aug-2021}) and can be used in further research.

翻译：与传统调查方法相比,Twitter等社交媒体平台为了解公众对气候变化的看法提供了巨大机会。 在本文中,我们构建了一个庞大的气候变化推特数据集,并利用机器学习进行了全面分析。通过进行主题建模和自然语言处理,我们展示了关于气候变化和主要气候事件的推文数量、人们讨论气候变化的共同主题以及情绪趋势之间的关系。我们的数据集在Kaggle上发表(\url{https://www.kaggle.com/leonsangguan/climate-change-tweets-ids-tue-aug-2021}),并可用于进一步研究。