Distinguishing Between Science and Action in Climate Discourse on Reddit

Mining climate conversations on social media has largely focused on identifying stance (pro, anti, or neutral), detecting misinformation, and analyzing sentiment and emotions. However, all pro-climate change posts are not monolithic; some emphasize scientific discoveries and facts (science-centric), while others propose solutions and actions (action-centric). Distinguishing between action and science posts can inform effective messaging and solutions to combat climate change. This paper leverages three climate-focused subreddits to explore the differences between science and action posts with respect to user engagement, sentiment analysis and classification potential. The findings reveal that engagement metrics differ significantly between action and science posts and both science and action posts show nearly balanced sentiment. Extensive experimentation with various machine learning models demonstrates that science and action posts can be distinguished with high performance. We explain these findings by considering the attitudes of the citizens, and hence, contribute to the body of knowledge through a nuanced understanding of online discourse on climate change. Furthermore, our work highlights the strengths and limitations of various NLP techniques in distinguishing between science and action-oriented climate messaging.