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Discussions on social media during major disasters are robust and often have multiple frames of reference. Temporal perspectives, however, are still lacking in current understandings of social-mediated discussions during disasters and crises, but incorporating temporal perspectives can significantly enhance environmental scanning efforts as prescribed in the issues management framework. The purpose of the current research is twofold: to apply and validate the SIR (Susceptible-Infectious-Recovered) model to examine topics' growth over time on social media and to understand how future orientation of social media users (an indicator of temporal distance) affects their construal of a disaster through supervised machine learning. We based our analysis on Twitter discussions during the Texas winter storm in 2021. Results of the study show great fit of the SIR model for topic growth, and that temporal distance affects users' construal of the event in line with core predictions of construal level theory. Theoretical, methodological, and practical implications on social-mediated discussions related to climate change-induced and -intensified disasters and issues management are discussed. • The current study used the infectious disease model to examine topic growth and identify rising topics. • The study incorporated a temporal perspective by modeling topic growth over time and individuals' future orientation. • Applying construal level theory, the study found that the differential growth rate corresponds to the centrality of the topic to the current disaster, with more central topics growing faster. • Temporal distance created a higher level of construal, focusing more on the central features of the event. • The methological approach is particularly relevant to issue monitoring and trend identification in issues management. [ABSTRACT FROM AUTHOR]