Mining Social Media to Identify Heat Waves

Francesca Cecinati, Tom Matthews, Sukumar Natarajan, Nick McCullen, David Coley

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.
Original languageEnglish
Article number762
Pages (from-to)1-19
Number of pages19
JournalInternational Journal of Environmental Research and Public Health
Volume16
Issue number5
DOIs
Publication statusPublished - 2 Mar 2019

Keywords

  • Heatwave
  • Heatwave definition
  • Social media
  • Twitter mining

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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