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社交媒体对热浪的反应。

Social media responses to heat waves.

作者信息

Jung Jihoon, Uejio Christopher K

机构信息

Department of Geography, Florida State University, Tallahassee, FL, USA.

Program in Public Health, Florida State University, Tallahassee, FL, USA.

出版信息

Int J Biometeorol. 2017 Jul;61(7):1247-1260. doi: 10.1007/s00484-016-1302-0. Epub 2017 Jan 11.

Abstract

Social network services (SNSs) may benefit public health by augmenting surveillance and distributing information to the public. In this study, we collected Twitter data focusing on six different heat-related themes (air conditioning, cooling center, dehydration, electrical outage, energy assistance, and heat) for 182 days from May 7 to November 3, 2014. First, exploratory linear regression associated outdoor heat exposure to the theme-specific tweet counts for five study cities (Los Angeles, New York, Chicago, Houston, and Atlanta). Next, autoregressive integrated moving average (ARIMA) time series models formally associated heat exposure to the combined count of heat and air conditioning tweets while controlling for temporal autocorrelation. Finally, we examined the spatial and temporal distribution of energy assistance and cooling center tweets. The result indicates that the number of tweets in most themes exhibited a significant positive relationship with maximum temperature. The ARIMA model results suggest that each city shows a slightly different relationship between heat exposure and the tweet count. A one-degree change in the temperature correspondingly increased the Box-Cox transformed tweets by 0.09 for Atlanta, 0.07 for Los Angeles, and 0.01 for New York City. The energy assistance and cooling center theme tweets suggest that only a few municipalities used Twitter for public service announcements. The timing of the energy assistance tweets suggests that most jurisdictions provide heating instead of cooling energy assistance.

摘要

社交网络服务(SNSs)可能通过加强监测和向公众传播信息来促进公众健康。在本研究中,我们收集了2014年5月7日至11月3日共182天的推特数据,重点关注六个不同的与高温相关的主题(空调、冷却中心、脱水、停电、能源援助和高温)。首先,进行探索性线性回归,将户外高温暴露与五个研究城市(洛杉矶、纽约、芝加哥、休斯顿和亚特兰大)特定主题的推文计数相关联。接下来,自回归积分移动平均(ARIMA)时间序列模型在控制时间自相关性的同时,将高温暴露与高温和空调推文的合并计数正式关联起来。最后,我们研究了能源援助和冷却中心推文的时空分布。结果表明,大多数主题的推文数量与最高温度呈现出显著的正相关关系。ARIMA模型结果表明,每个城市在高温暴露与推文计数之间的关系略有不同。温度每变化一度,亚特兰大经Box - Cox变换后的推文相应增加0.09,洛杉矶增加0.07,纽约市增加0.01。能源援助和冷却中心主题的推文表明,只有少数市政当局利用推特发布公共服务公告。能源援助推文的发布时间表明,大多数司法管辖区提供的是取暖能源援助而非制冷能源援助。

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