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• W2920297312 startingPage "762" @default.
• W2920297312 abstract "Heat waves are one of the deadliest of natural hazards and their frequency and intensity will likely increase as the climate continues to warm. A challenge in studying these phenomena is the lack of a universally accepted quantitative definition that captures both temperature anomalies and associated mortality. We test the hypothesis that social media mining can be used to identify heat wave mortality. Applying the approach to India, we find that the number of heat-related tweets correlates with heat-related mortality much better than traditional climate-based indicators, especially at larger scales, which identify many heat wave days that do not lead to excess mortality. We conclude that social media based heat wave identification can complement climatic data and can be used to: (1) study heat wave impacts at large scales or in developing countries, where mortality data are difficult to obtain and uncertain, and (2) to track dangerous heat wave events in real time." @default.
• W2920297312 created "2019-03-11" @default.
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• W2920297312 date "2019-03-02" @default.
• W2920297312 modified "2023-10-06" @default.
• W2920297312 title "Mining Social Media to Identify Heat Waves" @default.
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• W2920297312 doi "https://doi.org/10.3390/ijerph16050762" @default.
• W2920297312 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6427652" @default.
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• W2920297312 hasPublicationYear "2019" @default.
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