Increasing average temperatures and heat waves are having devasting impacts on human health and well-being but studies of heat impacts and how people adapt are rare and often confined to specific locations. In this study, we explore how analysis of conversations on social media can be used to understand how people feel about heat waves and how they respond. We collected global Twitter data over four months (from January to April 2022) using predefined hashtags about heat waves. Topic modelling identified five topics. The largest (one-third of all tweets) was related to sports events. The remaining two-thirds could be allocated to four topics connected to communication about climate-related heat or heat waves. Two of these were on the impacts of heat and heat waves (health impacts 20%; social impacts 16%), one was on extreme weather and climate change attribution (17%) and the last one was on perceptions and warning (13%). The number of tweets in each week corresponded well with major heat wave occurrences in Argentina, Australia, the USA and South Asia (India and Pakistan), indicating that people posting tweets were aware of the threat from heat and its impacts on the society. Among the words frequently used within the topic ‘Social impacts’ were ‘air-conditioning’ and ‘electricity’, suggesting links between coping strategies and financial pressure. Apart from analysing the content of tweets, new insights were also obtained from analysing how people engaged with Twitter tweets about heat or heat waves. We found that tweets posted early, and which were then shared by other influential Twitter users, were among the most popular. Finally, we found that the most popular tweets belonged to individual scientists or respected news outlets, with no evidence that misinformation about climate change-related heat is widespread.

In argument search, snippets provide an overview of the aspects discussed by the arguments retrieved for a queried controversial topic. Existing work has focused on generating snippets that are representative of an argument’s content while remaining argumentative. In this work, we argue that the snippets should also be contrastive, that is, they should highlight the aspects that make an argument unique in the context of others. Thereby, aspect diversity is increased and redundancy is reduced. We present and compare two snippet generation approaches that jointly optimize representativeness and contrastiveness. According to our experiments, both approaches have advantages, and one is able to generate representative yet sufficiently contrastive snippets.

Increasing average temperatures and heat waves have devasting impacts on human health and well-being but studies on heat impacts and how people adapt are rare and often confined to specific locations. In this study we aimed to explore how social media data can be used to generate knowledge about how people feel about heat waves through an analysis of their conversations. We collected global Twitter data over two months (January and February 2022) using predefined hashtags about heatwaves. Topic modelling revealed five clusters of which three were related to communications about climate change related heat, covering 76% of all tweets. These three clusters included one on the impacts of heat and heatwaves (34%), one on perceptions of weather and heat (28%) and one on extreme weather and climate change (14%). The remaining 24% of tweets were on sport events or films and music. The number of tweets in each week corresponded well with major heat wave occurrences in Argentina, Australia and India, indicating that people are aware of the threat from heat and its impacts on the society, although not much could be learned in terms of personal coping and preparedness strategies. Apart from the content of tweets, a great deal could be learned in terms of how people engaged with Twitter tweets about heat or heat waves. We found that tweets posted early, and which were shared by other influential Twitter users, were among the most popular. Finally, we found that the most popular tweets belonged to individual scientists or respected news outlets, with no evidence of wide-spread misinformation about climate change related heat.