Climate Campaign

Research on climate campaigns on social media focuses on understanding how messaging shapes public opinion and how to counter hate speech targeting climate activists. Current studies employ various machine learning techniques, including classical models like LGBM and Catboost, and advanced Large Language Models (LLMs) such as GPT-4, often enhanced by techniques like ensemble methods and data augmentation, to analyze themes, sentiment, and stance detection within social media data. These analyses provide valuable insights into the effectiveness of different campaign strategies, the spread of misinformation, and the dynamics of online polarization surrounding climate change. This work contributes to a better understanding of online discourse and informs the development of more effective climate communication strategies.