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Mining social media to identify heat waves

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journal contribution
posted on 2019-03-11, 14:53 authored by Francesca Cecinati, Tom Matthews, Sukumar Natarajan, Nick McCullen, David Coley
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.

Funding

This research was funded by EPSRC, grant number EP/R008612/1.

History

School

  • Social Sciences

Department

  • Geography and Environment

Published in

International Journal of Environmental Research and Public Health

Citation

CECINATI, F. ... et al, 2019. Mining social media to identify heat waves. International Journal of Environmental Research and Public Health, 16 (5), 762.

Publisher

MDPI AG © The Authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

2019-02-25

Publication date

2019-03-02

Notes

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

eISSN

1660-4601

Language

  • en

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