  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.
