Trend and Thoughts: Understanding Climate Change Concern using Machine Learning and Social Media Data
This provides a scalable alternative to traditional surveys for monitoring climate change concern, but it is incremental as it applies existing methods to new social media data.
The authors tackled the problem of understanding public opinion on climate change by constructing a massive Twitter dataset and analyzing it with machine learning, showing relationships between tweet volume and climate events, common topics, and sentiment trends.
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.