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Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy

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  • Bairong Wang

    (University at Buffalo)

  • Jun Zhuang

    (University at Buffalo)

Abstract

Social media has been widely used for crisis communication during disasters, and its use during extreme events has drawn attention from both researchers and practitioners. Although crisis information coverage and distribution speed are important issues, both have not been studied extensively in the literature. This paper fills this gap by studying information distribution and coverage of social media during disasters. To this end, we searched and analyzed 986,579 tweets posted during Hurricane Sandy (October 22 to November 6, 2012). To learn about responses from official agents, we sampled 163 governmental organizations (GO), 31 non-governmental organizations (NGO) and 276 news agent accounts and their tweets for analysis. Specifically, five social media key performance indicators (KPIs) are studied in this paper, including impression, like, mention, re-tweet, and response time, and other variables such as hashtag, tweet frequency, and information type. We also test whether the five KPIs and other variables are different among different user types. Results show that total impression, re-tweet rate, hashtag, and tweet frequency are significantly $$(P

Suggested Citation

  • Bairong Wang & Jun Zhuang, 2017. "Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy," 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. 89(1), pages 161-181, October.
    • Handle: RePEc:spr:nathaz:v:89:y:2017:i:1:d:10.1007_s11069-017-2960-x
    DOI: 10.1007/s11069-017-2960-x
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    References listed on IDEAS

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    1. Geoffrey Barbier & Reza Zafarani & Huiji Gao & Gabriel Fung & Huan Liu, 2012. "Maximizing benefits from crowdsourced data," Computational and Mathematical Organization Theory, Springer, vol. 18(3), pages 257-279, September.
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    Cited by:

    1. Jiang, Meiling & Gao, Qingwu & Zhuang, Jun, 2021. "Reciprocal spreading and debunking processes of online misinformation: A new rumor spreading–debunking model with a case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.
    3. Alekh Gour & Shikha Aggarwal & Subodha Kumar, 2022. "Lending ears to unheard voices: An empirical analysis of user‐generated content on social media," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2457-2476, June.
    4. Bairong Wang & Bin Liu & Qi Zhang, 2021. "An empirical study on Twitter’s use and crisis retweeting dynamics amid Covid-19," 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 2319-2336, July.
    5. Seungil Yum, 2021. "The effects of Hurricane Dorian on spatial reactions and mobility," 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. 105(3), pages 2481-2497, February.
    6. Nicole Olynk Widmar & Kendra Rash & Courtney Bir & Benjamin Bir & Jinho Jung, 2022. "The anatomy of natural disasters on online media: hurricanes and wildfires," 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. 110(2), pages 961-998, January.
    7. Sarah Gardiner & Jinyan Chen & Margarida Abreu Novais & Karine Dupré & J. Guy Castley, 2023. "Analyzing and Leveraging Social Media Disaster Communication of Natural Hazards: Community Sentiment and Messaging Regarding the Australian 2019/20 Bushfires," Societies, MDPI, vol. 13(6), pages 1-20, May.
    8. Cole Vaughn, 2024. "Evaluating elements of risk communication in risk messaging from officials on Twitter in the 2021 Marshall fire," 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. 120(6), pages 5537-5560, April.
    9. 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.
    10. Wu, Chunying & Xiong, Xiong & Gao, Ya & Zhang, Jin, 2022. "Does social media distort price discovery? Evidence from rumor clarifications," Research in International Business and Finance, Elsevier, vol. 62(C).
    11. Shan-e-hyder Soomro & Muhammad Waseem Boota & Xiaotao Shi & Gul-e-Zehra Soomro & Yinghai Li & Muhammad Tayyab & Caihong Hu & Chengshuai Liu & Yuanyang Wang & Junaid Abdul Wahid & Mairaj Hyder Alias Aa, 2024. "Appraisal of Urban Waterlogging and Extent Damage Situation after the Devastating Flood," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(12), pages 4911-4931, September.
    12. Sungyoon Kim & Wanyun Shao & Jonghun Kam, 2019. "Spatiotemporal patterns of US drought awareness," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    13. 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.
    14. Cole Vaughn & Kathleen Sherman-Morris & Philip Poe, 2023. "Factors influencing retweeting of local news media tweets during Hurricane Irma," 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. 119(1), pages 583-611, October.
    15. Paul M. Johnson & Corey E. Brady & Craig Philip & Hiba Baroud & Janey V. Camp & Mark Abkowitz, 2020. "A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1795-1810, September.
    16. Bairong Wang & Jun Zhuang, 2018. "Rumor response, debunking response, and decision makings of misinformed Twitter users during disasters," 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. 93(3), pages 1145-1162, September.
    17. Gabrielle Turner-McGrievy & Amir Karami & Courtney Monroe & Heather M. Brandt, 2020. "Dietary pattern recognition on Twitter: a case example of before, during, and after four natural disasters," 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. 103(1), pages 1035-1049, August.
    18. Türkay Dereli & Nazmiye Eligüzel & Cihan Çetinkaya, 2021. "Content analyses of the international federation of red cross and red crescent societies (ifrc) based on machine learning techniques through twitter," 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. 106(3), pages 2025-2045, April.
    19. Mingyun Gu & Haixiang Guo & Jun Zhuang & Yufei Du & Lijin Qian, 2022. "Social Media User Behavior and Emotions during Crisis Events," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    20. Carine Dominguez-Péry & Rana Tassabehji & Lakshmi Narasimha Raju Vuddaraju & Vikhram Kofi Duffour, 2021. "Improving emergency response operations in maritime accidents using social media with big data analytics: a case study of the MV Wakashio disaster," Post-Print hal-04021179, HAL.
    21. Martínez-Rojas, María & Pardo-Ferreira, María del Carmen & Rubio-Romero, Juan Carlos, 2018. "Twitter as a tool for the management and analysis of emergency situations: A systematic literature review," International Journal of Information Management, Elsevier, vol. 43(C), pages 196-208.
    22. Kyle Hunt & Bairong Wang & Jun Zhuang, 2020. "Misinformation debunking and cross-platform information sharing through Twitter during Hurricanes Harvey and Irma: a case study on shelters and ID checks," 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. 103(1), pages 861-883, August.

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