Department of Architecture and Civil Engineering, University of Bath, Bath BA2 7AY, UK.
Department of Geography and Environment, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
Int J Environ Res Public Health. 2019 Mar 2;16(5):762. doi: 10.3390/ijerph16050762.
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.
热浪是最致命的自然灾害之一，随着气候持续变暖，其频率和强度可能会增加。研究这些现象的一个挑战是缺乏普遍接受的定量定义，该定义既可以捕捉温度异常，也可以捕捉相关死亡率。我们检验了这样一个假设，即社交媒体挖掘可以用于识别热浪导致的死亡。我们将该方法应用于印度，发现与与热相关的推文数量与与热相关的死亡率相关性更好，明显优于传统的基于气候的指标，尤其是在更大的范围内，这些指标可以识别出许多不会导致超额死亡的热浪日。我们得出的结论是，基于社交媒体的热浪识别可以补充气候数据，并可用于：(1) 在死亡率数据难以获取且不确定的情况下，在大规模或发展中国家研究热浪的影响，(2) 实时跟踪危险的热浪事件。
