The climate and ecological crisis in which we are living requires prompt interventions by policymakers worldwide. Countries are now implementing emission reduction policies, while people orient their attitudes and behaviors towards personal decarbonization. It is, thus, crucial to understand whether public opinion and the countries’ policies align in this effort. To do so, we downloaded a sample of 2924 tweets regarding the green transition by the general Italian population. Performances of two state-of-the-art sentiment analysis models (i.e., Valence Aware Dictionary for Sentiment Reasoning (VADER) and multilingual RoBERTa sentiment (XLM-T)) were initially compared on a sample of 100 manually labeled tweets. Subsequently, BERTopic was used to identify the main topics of discussion in tweets. Ultimately, the best-performing sentiment analysis model was applied to each theme of discussion to identify specific sentiments of the Italian population. From the results, XLM-T outperformed VADER. Furthermore, 9 main topics of discussion were identified. In almost all topics, sentiments resulted to be predominantly negative or neutral. The current results suggest the need for more dialogues between policymakers and the general population in order to align the effort in facing the climate crisis.