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

Author

Listed:
  • 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
    Department of Dermatology, Venerology and Allergology, Charité—Universitätsmedizin Berlin, 10117 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
    Epidemiology, Biostatistics and Prevention Institute, University of Zurich, 8001 Zurich, Switzerland)

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.

Suggested Citation

  • Sonja I. Garske & Suzanne Elayan & Martin Sykora & Tamar Edry & Linus B. Grabenhenrich & Sandro Galea & Sarah R. Lowe & Oliver Gruebner, 2021. "Space-Time Dependence of Emotions on Twitter after a Natural Disaster," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:10:p:5292-:d:555665
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    References listed on IDEAS

    as
    1. Yury Kryvasheyeu & Haohui Chen & Esteban Moro & Pascal Van Hentenryck & Manuel Cebrian, 2015. "Performance of Social Network Sensors during Hurricane Sandy," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
    2. Lowe, Sarah R. & Joshi, Spruha & Pietrzak, Robert H. & Galea, Sandro & Cerdá, Magdalena, 2015. "Mental health and general wellness in the aftermath of Hurricane Ike," Social Science & Medicine, Elsevier, vol. 124(C), pages 162-170.
    3. Dajun Dai & Ruixue Wang, 2020. "Space-Time Surveillance of Negative Emotions after Consecutive Terrorist Attacks in London," IJERPH, MDPI, vol. 17(11), pages 1-15, June.
    4. Sinnenberg, L. & Buttenheim, A.M. & Padrez, K. & Mancheno, C. & Ungar, L. & Merchant, R.M., 2017. "Twitter as a tool for health research: A systematic review," American Journal of Public Health, American Public Health Association, vol. 107(1), pages 1-8.
    5. Yan Wang & John E. Taylor, 2018. "Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa Earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(2), pages 907-925, June.
    6. Oliver Gruebner & Sarah R. Lowe & Martin Sykora & Ketan Shankardass & SV Subramanian & Sandro Galea, 2018. "Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media," IJERPH, MDPI, vol. 15(10), pages 1-12, October.
    7. Sarah R Lowe & Laura Sampson & Oliver Gruebner & Sandro Galea, 2015. "Psychological Resilience after Hurricane Sandy: The Influence of Individual- and Community-Level Factors on Mental Health after a Large-Scale Natural Disaster," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-15, May.
    8. repec:aph:ajpbhl:10.2105/ajph.2016.303512_4 is not listed on IDEAS
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    Cited by:

    1. Joel Oommen George & Suzanne Elayan & Martin Sykora & Marin Solter & Rob Feick & Christopher Hewitt & Yiqiao Liu & Ketan Shankardass, 2023. "The Role of Social Media in Building Pandemic Resilience in an Urban Community: A Qualitative Case Study," IJERPH, MDPI, vol. 20(17), pages 1-18, September.
    2. Seungil Yum, 2023. "Analyses of human responses to Winter storm Kai using the GWR model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(2), pages 1805-1821, March.
    3. Lennart Reifels & Michel L. A. Dückers, 2023. "Disaster Mental Health Risk Reduction: Appraising Disaster Mental Health Research as If Risk Mattered," IJERPH, MDPI, vol. 20(11), pages 1-14, May.
    4. Shi Shen & Ke Shi & Junwang Huang & Changxiu Cheng & Min Zhao, 2023. "Global online social response to a natural disaster and its influencing factors: a case study of Typhoon Haiyan," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.

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