Mining Social Media to Identify Heat Waves

Francesca Cecinati, Tom Matthews, Sukumar Natarajan, Nick McCullen and David Coley
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Francesca Cecinati: Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7AY, UK
Tom Matthews: Department of Geography and Environment, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK
Sukumar Natarajan: Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7AY, UK
Nick McCullen: Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7AY, UK
David Coley: Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7AY, UK

IJERPH, 2019, vol. 16, issue 5, 1-19

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.

Keywords: heatwave; heatwave definition; Twitter mining; social media (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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