Social media is widely used in emergencies, but the nature of the communication is poorly understood. We employed unsupervised topic modelling and sentiment analysis to analyse more than 80,000 Twitter tweets posted by users in Australia over a six-month period before, during and after the severe bushfires in 2019–2020, dubbed the ‘Black Summer’. While tweets about bushfire updates dominated, politics, donations and support, impacts and public opinion were also prominent themes. Social impacts were important in the early phase of the fires (Sept & Oct 2019) with health impacts discussed when the fires were most intense and ecological impacts becoming important in the recovery phase. Twitter users also talked about emergency responses, mainly evacuation, as the fires were starting, showing that Twitter played an important role in communicating advice to leave early to avoid harm. Although the bushfires caused death, destruction and disruption, the sentiment of tweets was balanced − 40% of all tweets were positive, 36% negative and the remainder neutral (24%). Sentiments shifted little over time, but some topics were strongly associated with the expression of negative sentiments. The unusual severity of the fires was attributed to climate change in the early and recovery phases but misinformation about arson as a cause briefly diverted attention from climate change in the middle. Twitter was used to express anger about a lack of action by the Australian government to address climate change. Unexpectedly, Twitter users from the most affected areas were more likely to post positive tweets than those further away, particular during recovery, suggesting both resilience and gratitude for support provided to them. Analysis of trend data on Twitter using machine learning has the potential to identify, in real time, whether appropriate messages are reaching and being disseminated effectively, provide early warning of potentially harmful misinformation and, if undertaken repeatedly, provide a metric against which responses to fire can be measured.