Department of Geography, Humboldt-Universität zu Berlin, Berlin 10099, Germany.
Epidemiology, Biostatistics, and Prevention Institute (EBPI), University of Zurich, 8001 Zurich, Switzerland.
Int J Environ Res Public Health. 2018 Oct 17;15(10):2275. doi: 10.3390/ijerph15102275.
Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. Our sample consisted of 1,018,140 geo-located tweets that were analyzed with an advanced sentiment analysis called "Extracting the Meaning Of Terse Information in a Visualization of Emotion" (EMOTIVE). We calculated discomfort rates for 2137 NYC census tracts, applied spatial regimes regression to find associations of discomfort, and used Moran's I for spatial cluster detection across NYC boroughs over time. We found increased discomfort, that is, bundled negative emotions after the storm as compared to during the storm. Furthermore, pre- and peri-disaster discomfort was positively associated with post-disaster discomfort; however, this association was different across boroughs, with significant associations only in Manhattan, the Bronx, and Queens. In addition, rates were most prominently spatially clustered in Staten Island lasting pre- to post-disaster. This is the first study that determined significant associations of negative emotional responses found in social media posts over space and time in the context of a natural disaster, which may guide us in identifying those areas and populations mostly in need for care.
灾害对人口心理健康有重大影响。我们使用 Twitter 来：(1) 在 2012 年超级风暴桑迪发生之前、期间和之后，从纽约市（NYC）提取表明不适的负面情绪。我们进一步旨在：(2) 确定预先或灾害期间的不适是否分别与预先或灾害后的不适相关，以及 (3) 评估随着时间的推移，NYC 人口普查区之间不适的地理差异。我们的样本由 1,018,140 个地理定位的推文组成，这些推文通过一种名为“在情感可视化中提取简洁信息的含义”（EMOTIVE）的高级情感分析进行了分析。我们计算了 2137 个 NYC 人口普查区的不适率，应用空间规则回归来发现不适的关联，并使用 Moran's I 来检测随着时间的推移在 NYC 行政区之间的空间聚类。我们发现，与风暴期间相比，风暴后不适程度更高，即负面情绪更加集中。此外，预先和灾害期间的不适与灾害后的不适呈正相关；然而，这种关联在行政区之间存在差异，仅在曼哈顿、布朗克斯和皇后区存在显著关联。此外，在整个灾害期间，斯塔顿岛的不适率在空间上最为明显且呈聚类分布。这是第一项确定社交媒体帖子中负面情绪反应在自然灾害背景下的空间和时间上的显著关联的研究，这可能有助于我们确定那些最需要关注的地区和人群。
