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Performance of Social Network Sensors during Hurricane Sandy

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  • Yury Kryvasheyeu
  • Haohui Chen
  • Esteban Moro
  • Pascal Van Hentenryck
  • Manuel Cebrian

Abstract

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the “friendship paradox”, is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users’ network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple “sentiment sensing” technique that can detect and locate disasters.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0117288
    DOI: 10.1371/journal.pone.0117288
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    1. Quirin Schiermeier, 2006. "Insurers' disaster files suggest climate is culprit," Nature, Nature, vol. 441(7094), pages 674-674, June.
    2. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    4. Manuel Garcia-Herranz & Esteban Moro & Manuel Cebrian & Nicholas A Christakis & James H Fowler, 2014. "Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-7, April.
    5. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    6. Seth Cooper & Firas Khatib & Adrien Treuille & Janos Barbero & Jeehyung Lee & Michael Beenen & Andrew Leaver-Fay & David Baker & Zoran Popović & Foldit players, 2010. "Predicting protein structures with a multiplayer online game," Nature, Nature, vol. 466(7307), pages 756-760, August.
    7. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
    8. Dirk Helbing & Pratik Mukerji, "undated". "Crowd Disasters as Systemic Failures: Analysis of the Love Parade Disaster," Working Papers ETH-RC-12-010, ETH Zurich, Chair of Systems Design.
    9. Bryn Nelson, 2013. "Natural disasters: A calculated risk," Nature, Nature, vol. 495(7440), pages 271-273, March.
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    Cited by:

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    2. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.
    3. Simandjuntak, Daniel P. & Jaenicke, Edward C. & Wrenn, Douglas H., 2022. "Heterogeneity in Consumer Food Stockpiling and Retailer Experiences During Hurricane Sandy," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322183, Agricultural and Applied Economics Association.
    4. Rachel Samuels & Jiajia Xie & Neda Mohammadi & John E. Taylor, 2022. "Tipping the scales: how geographical scale affects the interpretation of social media behavior in crisis research," 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. 112(1), pages 545-564, May.
    5. Xiangyang Guan & Cynthia Chen & Dan Work, 2016. "Tracking the Evolution of Infrastructure Systems and Mass Responses Using Publically Available Data," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-17, December.
    6. M. R. Mahendrini Fernando Ariyachandra & Gayan Wedawatta, 2023. "Digital Twin Smart Cities for Disaster Risk Management: A Review of Evolving Concepts," Sustainability, MDPI, vol. 15(15), pages 1-25, August.
    7. 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.

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