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Social media usage reveals recovery of small businesses after natural hazard events

Author

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  • Robert Eyre

    (University of Bristol, Department of Engineering Mathematics)

  • Flavia De Luca

    (University of Bristol, Department of Civil Engineering)

  • Filippo Simini

    (University of Bristol, Department of Engineering Mathematics
    The Alan Turing Institute)

Abstract

The challenge of nowcasting the effect of natural hazard events (e.g., earthquakes, floods, hurricanes) on assets, people and society is of primary importance for assessing the ability of such systems to recover from extreme events. Traditional recovery estimates, such as surveys and interviews, are usually costly, time consuming and do not scale. Here we present a methodology to indirectly estimate the post-emergency recovery status (downtime) of small businesses in urban areas looking at their online posting activity on social media. Analysing the time series of posts before and after an event, we quantify the downtime of small businesses for three natural hazard events occurred in Nepal, Puerto Rico and Mexico. A convenient and reliable method for nowcasting the post-emergency recovery status of economic activities could help local governments and decision makers to better target their interventions and distribute the available resources more effectively.

Suggested Citation

  • Robert Eyre & Flavia De Luca & Filippo Simini, 2020. "Social media usage reveals recovery of small businesses after natural hazard events," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15405-7
    DOI: 10.1038/s41467-020-15405-7
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    Cited by:

    1. Yu, Ling & Zhao, Pengjun & Tang, Junqing & Pang, Liang, 2023. "Changes in tourist mobility after COVID-19 outbreaks," Annals of Tourism Research, Elsevier, vol. 98(C).
    2. Bouzahzah, Mohamed, 2020. "Méthodes quantitatives et prévisions économiques en période de crise. Intérêt et limites [Quantitative methods and economic forecasts in times of crisis. Interest and limits]," MPRA Paper 113227, University Library of Munich, Germany.
    3. Chenchen Yang & Han Zhang & Xunhua Li & Zongyi He & Junli Li, 2023. "Analysis of spatial and temporal characteristics of major natural disasters in China from 2008 to 2021 based on mining news database," 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(3), pages 1881-1916, September.
    4. Silvio Cristiano & Francesco Gonella, 2020. "‘Kill Venice’: a systems thinking conceptualisation of urban life, economy, and resilience in tourist cities," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    5. Kaixin Zhu & Zhifeng Cheng & Jianghao Wang, 2024. "Measuring Chinese mobility behaviour during COVID-19 using geotagged social media data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    6. Yao, Wenbin & Chen, Nuo & Su, Hongyang & Hu, Youwei & Jin, Sheng & Rong, Donglei, 2023. "A novel self-adaption macroscopic fundamental diagram considering network heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    7. Takahiro Yabe & P Suresh C Rao & Satish V Ukkusuri, 2021. "Regional differences in resilience of social and physical systems: Case study of Puerto Rico after Hurricane Maria," Environment and Planning B, , vol. 48(5), pages 1042-1057, June.
    8. Siqing Shan & Feng Zhao, 2023. "Social media-based urban disaster recovery and resilience analysis of the Henan deluge," 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(1), pages 377-405, August.

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