TY  - JOUR
PY  - 2019//
TI  - Mining social media to identify heat waves
JO  - International journal of environmental research and public health
A1  - Cecinati, Francesca
A1  - Matthews, Tom
A1  - Natarajan, Sukumar
A1  - McCullen, Nick
A1  - Coley, David
SP  - e16050762
EP  - e16050762
VL  - 16
IS  - 5
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 1661-7827
UR  - http://dx.doi.org/10.3390/ijerph16050762
ID  - ref1
ER  -