title: Social media responses to heat waves.
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.
authors.affiliation: Department of Geography, Florida State University, Tallahassee, FL, USA. climategeo@gmail.com.
authors.forename: Jihoon
authors.identifier: http://orcid.org/0000-0002-3757-4783
authors.initials: J
authors.lastname: Jung
authors.affiliation: Department of Geography, Florida State University, Tallahassee, FL, USA.|Program in Public Health, Florida State University, Tallahassee, FL, USA.
authors.forename: Christopher K
authors.initials: CK
authors.lastname: Uejio
mesh_terms: D000389:Air Conditioning; D002947:Cities; D003681:Dehydration; D055874:Extreme Heat; D006801:Humans; D008962:Models, Theoretical; D061108:Social Media; D014481:United States
keywords: ARIMA; Cooling center; Energy assistance; Heat wave; Social media; Time series