Space-Time Dependence of Emotions on Twitter after a Natural Disaster

Sonja I. Garske, Suzanne Elayan, Martin Sykora, Tamar Edry, Linus B. Grabenhenrich, Sandro Galea, Sarah R. Lowe and Oliver Gruebner
Additional contact information
Sonja I. Garske: State Office of Health and Social Affairs, 10639 Berlin, Germany
Suzanne Elayan: Centre for Information Management, Loughborough University, Leicestershire LE11 3TU, UK
Martin Sykora: Centre for Information Management, Loughborough University, Leicestershire LE11 3TU, UK
Tamar Edry: Department of Geography, University of Zurich, 8057 Zurich, Switzerland
Linus B. Grabenhenrich: Department for Methodology and Research Infrastructure, Robert Koch-Institut, 13359 Berlin, Germany
Sandro Galea: School of Public Health, Boston University, Boston, MA 02118, USA
Sarah R. Lowe: Department of Social & Behavioral Sciences, Yale School of Public Health, New Haven, CT 06510, USA
Oliver Gruebner: Department of Geography, University of Zurich, 8057 Zurich, Switzerland

IJERPH, 2021, vol. 18, issue 10, 1-13

Abstract: Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations between socioeconomic status and infrastructural damage with negative emotional expressions across NYC census tracts over time. A total of 984,311 geo-referenced tweets with negative basic emotions (anger, disgust, fear, sadness, shame) were collected and assigned to the census tracts within NYC boroughs between 8 October and 18 November 2012. Global and local univariate and bivariate Moran’s I statistics were used to analyze the data. We found local spatial clusters of all negative emotions over all disaster periods. Socioeconomic status and infrastructural damage were predominantly correlated with disgust, fear, and shame post-disaster. We identified spatial clusters of emotional reactions during and in the aftermath of a large-scale disaster that could help provide guidance about where immediate and long-term relief measures are needed the most, if transferred to similar events and on comparable data worldwide.

Keywords: natural disaster; post disaster mental health; digital epidemiology; spatial epidemiology; health geography; Twitter (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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