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Social media information sharing for natural disaster response

Author

Listed:
  • Zhijie Sasha Dong

    (Texas State University)

  • Lingyu Meng

    (Texas State University)

  • Lauren Christenson

    (Texas State University)

  • Lawrence Fulton

    (Texas State University)

Abstract

Social media has become an essential channel for posting disaster-related information, which provides governments and relief agencies real-time data for better disaster management. However, research in this field has not received sufficient attention, and extracting useful information is still challenging. This paper aims to improve disaster relief efficiency via mining and analyzing social media data like public attitudes toward disaster response and public demands for targeted relief supplies during different types of disasters. We focus on different natural disasters based on properties such as types, durations, and damages, which contains a total of 41,993 tweets. In this paper, public perception is assessed qualitatively by manually classified tweets, which contain information like the demand for targeted relief supplies, satisfactions of disaster response, and public fear. Public attitudes to natural disasters are studied via a quantitative analysis using eight machine learning models. To better provide decision-makers with the appropriate model, the comparison of machine learning models based on computational time and prediction accuracy is conducted. The change of public opinion during different natural disasters and the evolution of peoples’ behavior of using social media for disaster relief in the face of the identical type of natural disasters as Twitter continues to evolve are studied. The results in this paper demonstrate the feasibility and validation of the proposed research approach and provide relief agencies with insights into better disaster management.

Suggested Citation

  • Zhijie Sasha Dong & Lingyu Meng & Lauren Christenson & Lawrence Fulton, 2021. "Social media information sharing for natural disaster response," 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. 107(3), pages 2077-2104, July.
  • Handle: RePEc:spr:nathaz:v:107:y:2021:i:3:d:10.1007_s11069-021-04528-9
    DOI: 10.1007/s11069-021-04528-9
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jia He & Miao Ma & Yuxuan Zhou & Miaoke Wang, 2023. "What We Have Learned about the Characteristics and Differences of Disaster Information Behavior in Social Media—A Case Study of the 7.20 Henan Heavy Rain Flood Disaster," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    2. Brielle Lillywhite & Gregor Wolbring, 2022. "Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review," Sustainability, MDPI, vol. 14(20), pages 1-50, October.
    3. U. Bala Aiswarya & R. M. Harindranath & Praseeda Challapalli, 2024. "Social Media Information Sharing: Is It a Catalyst for Green Consumption among Gen X and Gen Y Cohorts?," Sustainability, MDPI, vol. 16(14), pages 1-22, July.
    4. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    5. Zribi, Wissal & Boufateh, Talel & Guesmi, Khaled, 2023. "Climate uncertainty effects on bitcoin ecological footprint through cryptocurrency environmental attention," Finance Research Letters, Elsevier, vol. 58(PD).
    6. Turgut Acikara & Bo Xia & Tan Yigitcanlar & Carol Hon, 2023. "Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature," Sustainability, MDPI, vol. 15(11), pages 1-50, May.
    7. 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.
    8. Hamid Bahadori & Hamed Vahdat-Nejad & Hossein Moradi, 2022. "CrowdBIG: crowd-based system for information gathering from the earthquake environment," 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. 114(3), pages 3719-3741, December.

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