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Social media for enhanced understanding of disaster resilience during Hurricane Florence

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  • Yuan, Faxi
  • Li, Min
  • Liu, Rui
  • Zhai, Wei
  • Qi, Bing

Abstract

Citizens with different demographic characters presented varying responses and behaviors in the same disasters. Their divergent responses can impact their actual damages during crises. Previous studies have employed social media for analyzing citizens’ crisis responses. However, these studies missed the demographic dimension. To resolve this limitation, this research proposes three objectives: 1) to explore the variances of sentiment polarities among different racial/ethnic and gender groups; 2) to investigate the concern themes in their expressions, including theme popularity and their sentiment towards these themes; 3) to enhance the understanding of social aspects of disaster resilience with the results of disaster response disparities. Results indicate that Hispanic and male groups are more likely to express negative sentiment. The black group pays the least attention to ‘hurricane warn’ and shows most interests in ‘pray/donate’. The white group is most optimistic about hurricane/flood impacts while the black group shows dissatisfaction towards ‘response’. The female group pays less attention to ‘hurricane warn’ while they are more optimistic towards ‘hurricane/flood impact’ and ‘response’ than the male group. Our findings can help crisis response managers identify the more sensitive/vulnerable groups in the crisis and provide on-target disaster evolution reports and relief resources to the corresponding demographic groups.

Suggested Citation

  • Yuan, Faxi & Li, Min & Liu, Rui & Zhai, Wei & Qi, Bing, 2021. "Social media for enhanced understanding of disaster resilience during Hurricane Florence," International Journal of Information Management, Elsevier, vol. 57(C).
  • Handle: RePEc:eee:ininma:v:57:y:2021:i:c:s0268401220314882
    DOI: 10.1016/j.ijinfomgt.2020.102289
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    Citations

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    Cited by:

    1. Muhammad Ashraf Fauzi, 2023. "Social media in disaster management: review of the literature and future trends through bibliometric analysis," 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. 118(2), pages 953-975, September.
    2. Ewa Lechowska, 2022. "Approaches in research on flood risk perception and their importance in flood risk management: a review," 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. 111(3), pages 2343-2378, April.
    3. Achraf Tounsi & Marouane Temimi, 2023. "A systematic review of natural language processing applications for hydrometeorological hazards assessment," 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(3), pages 2819-2870, April.
    4. Peng Chen & Wei Zhai & Xiankui Yang, 2023. "Enhancing resilience and mobility services for vulnerable groups facing extreme weather: lessons learned from Snowstorm Uri in Harris County, Texas," 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. 118(2), pages 1573-1594, September.
    5. 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.

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