IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v112y2022i1d10.1007_s11069-021-05193-8.html
   My bibliography  Save this article

Tipping the scales: how geographical scale affects the interpretation of social media behavior in crisis research

Author

Listed:
  • Rachel Samuels

    (Georgia Institute of Technology)

  • Jiajia Xie

    (Georgia Institute of Technology)

  • Neda Mohammadi

    (Georgia Institute of Technology)

  • John E. Taylor

    (Georgia Institute of Technology)

Abstract

Our relationship with technology is constantly evolving, and how we use technology in disasters has evolved even faster. Understanding how to utilize human interactions with technology and the limitations of those interactions will be a crucial building block to contextualizing crisis data. The impact of geographic scale on behavioral change analyses is an unexplored facet of our ability to identify relative severities of crisis situations, magnitudes of localized crises, and total durations of disaster impacts. Within this paper, we aggregate Twitter and hurricane damage data across a wide range of geographic scales and assess the impact of increasing scale on both the recognition of extreme behaviors and the correlation between activity and damage. The power-law relationships identified between many of these variables indicate a direct, definable scalar dependence of social media aggregation analyses, and these relationships can be used to inform more intelligent, equitable, and actionable social media usage in emergency response.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:112:y:2022:i:1:d:10.1007_s11069-021-05193-8
    DOI: 10.1007/s11069-021-05193-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-05193-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-021-05193-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    3. Xiangyang Guan & Cynthia Chen, 2014. "Using social media data to understand and assess 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. 74(2), pages 837-850, November.
    4. Rachel Samuels & John E. Taylor & Neda Mohammadi, 2020. "Silence of the Tweets: incorporating social media activity drop-offs into crisis detection," 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 1455-1477, August.
    5. Cynthia Chen & Dave Neal & Mengchu Zhou, 2013. "Understanding the evolution of a disaster—a Framework for Assessing Crisis in a System Environment (FACSE)," 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. 65(1), pages 407-422, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Rachel Samuels & John E. Taylor & Neda Mohammadi, 2020. "Silence of the Tweets: incorporating social media activity drop-offs into crisis detection," 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 1455-1477, August.
    3. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    4. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    5. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    6. Hansen, Lars Peter & Heaton, John & Luttmer, Erzo G J, 1995. "Econometric Evaluation of Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 237-274.
    7. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    8. Luis Garicano & Thomas N. Hubbard, 2016. "The Returns to Knowledge Hierarchies," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 32(4), pages 653-684.
    9. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    10. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2020. "The information content of funds from operations and net income in real estate investment trusts," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. Downward, Paul & Rasciute, Simona, 2015. "Assessing the impact of the National Cycle Network and physical activity lifestyle on cycling behaviour in England," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 425-437.
    12. Filiz-Ozbay, Emel & Guryan, Jonathan & Hyndman, Kyle & Kearney, Melissa & Ozbay, Erkut Y., 2015. "Do lottery payments induce savings behavior? Evidence from the lab," Journal of Public Economics, Elsevier, vol. 126(C), pages 1-24.
    13. repec:lan:wpaper:2935 is not listed on IDEAS
    14. Subir K. Chakrabarti & Srikant Devaraj & Pankaj C. Patel, 2021. "Minimum wage and restaurant hygiene violations: Evidence from Seattle," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 85-99, January.
    15. Coll Martínez, Eva & Arauzo Carod, Josep Maria, 2015. "Creative Industries: a Preliminary Insight to their Location Determinants," Working Papers 2072/250133, Universitat Rovira i Virgili, Department of Economics.
    16. Mohammed Abdellaoui & Olivier L’Haridon & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Journal of Risk and Uncertainty, Springer, vol. 41(1), pages 39-65, August.
    17. Christopher Jeffords, 2014. "Preference-directed regulation when ethical environmental policy choices are formed with limited information," Empirical Economics, Springer, vol. 46(2), pages 573-606, March.
    18. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    19. Corradi, Valentina & Swanson, Norman R., 2004. "A test for the distributional comparison of simulated and historical data," Economics Letters, Elsevier, vol. 85(2), pages 185-193, November.
    20. Tue Gørgens & Dean Robert Hyslop, 2018. "The Specification of Dynamic Discrete-Time Two-State Panel Data Models," Econometrics, MDPI, vol. 7(1), pages 1-16, December.
    21. Christopher J. W. Zorn, 1998. "An Analytic and Empirical Examination of Zero-Inflated and Hurdle Poisson Specifications," Sociological Methods & Research, , vol. 26(3), pages 368-400, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:112:y:2022:i:1:d:10.1007_s11069-021-05193-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.