IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v8y2021i1d10.1057_s41599-021-00914-7.html
   My bibliography  Save this article

Data-driven modeling reveals the Western dominance of global public interest in earthquakes

Author

Listed:
  • Jonghun Kam

    (Pohang University of Science and Technology
    Pohang University of Science and Technology (POSTECH)
    Yonsei University)

  • Jihun Park

    (Pohang University of Science and Technology (POSTECH))

  • Wanyun Shao

    (The University of Alabama)

  • Junho Song

    (The University of Alabama)

  • Jinhee Kim

    (Pohang University of Science and Technology)

  • Fabrizio Terenzio Gizzi

    (National Research Council (ISPC-CNR), Area della Ricerca, C.da S. Loja)

  • Donatella Porrini

    (University of Salento, Centro Ecotekne - Via per Monteroni)

  • Young-Joo Suh

    (Pohang University of Science and Technology (POSTECH))

Abstract

Catastrophic earthquakes stimulate information-seeking behaviors beyond the affected geographical boundaries; however, our understanding of the dynamics of global public interest in earthquakes remains limited. Herein, we harness Big Data to examine the dynamic patterns of global public interest, concerning 17 significant worldwide earthquakes over 2004–2019. We find that the global community shows a higher level of interest when an earthquake occurs in developed countries than in developing countries; however, they lose their interest in the former more rapidly than the latter. Regardless of the affected nation, there is a one- to two-week “golden” time window when attention can be leveraged for fundraising and humanitarian aid. Our findings suggest that European citizens who are highly interested in earthquakes emerge as a potential key community to achieve great inclusiveness in policy interventions to solicit international aid. The findings of this study hint at how Big Data can be utilized to identify “time windows of opportunities” for international humanitarian organizations to efficiently raise donations, charities, and aid resources around the world.

Suggested Citation

  • Jonghun Kam & Jihun Park & Wanyun Shao & Junho Song & Jinhee Kim & Fabrizio Terenzio Gizzi & Donatella Porrini & Young-Joo Suh, 2021. "Data-driven modeling reveals the Western dominance of global public interest in earthquakes," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-9, December.
    • Handle: RePEc:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00914-7
    DOI: 10.1057/s41599-021-00914-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-021-00914-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-021-00914-7?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. Michael Berlemann & Tobias Thomas, 2019. "The distance bias in natural disaster reporting – empirical evidence for the United States," Applied Economics Letters, Taylor & Francis Journals, vol. 26(12), pages 1026-1032, July.
    2. Tiodora Siagian & Purhadi Purhadi & Suhartono Suhartono & Hamonangan Ritonga, 2014. "Social vulnerability to natural hazards in Indonesia: driving factors and policy implications," 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. 70(2), pages 1603-1617, January.
    3. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    4. Jiuping Xu & Ying Wei, 2013. "Social Support as a Moderator of the Relationship between Anxiety and Depression: An Empirical Study with Adult Survivors of Wenchuan Earthquake," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    5. John McCloskey & Suleyman S. Nalbant & Sandy Steacy, 2005. "Earthquake risk from co-seismic stress," Nature, Nature, vol. 434(7031), pages 291-291, March.
    6. Sungyoon Kim & Wanyun Shao & Jonghun Kam, 2019. "Spatiotemporal patterns of US drought awareness," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    7. L N Van Wassenhove, 2006. "Humanitarian aid logistics: supply chain management in high gear," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 475-489, May.
    8. Fabrizio Terenzio Gizzi & Jonghun Kam & Donatella Porrini, 2020. "Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-11, December.
    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. Shi Shen & Ke Shi & Junwang Huang & Changxiu Cheng & Min Zhao, 2023. "Global online social response to a natural disaster and its influencing factors: a case study of Typhoon Haiyan," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.

    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. Fabrizio Terenzio Gizzi & Jonghun Kam & Donatella Porrini, 2020. "Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-11, December.
    2. Mioara, POPESCU, 2015. "Construction Of Economic Indicators Using Internet Searches," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 6(1), pages 25-31.
    3. CHEN, Helen S.Y., 2020. "Designing Sustainable Humanitarian Supply Chains," OSF Preprints m82ar, Center for Open Science.
    4. Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2020. "Measuring partisan media bias in US Newscasts from 2001-2012," Working Paper 183/2020, Helmut Schmidt University, Hamburg, revised 15 Nov 2022.
    5. Francesco Capozza & Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2021. "Studying Information Acquisition in the Field: A Practical Guide and Review," CEBI working paper series 21-15, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    6. Tommaso Colussi & Ingo E. Isphording & Nico Pestel, 2021. "Minority Salience and Political Extremism," American Economic Journal: Applied Economics, American Economic Association, vol. 13(3), pages 237-271, July.
    7. David W Carter & Scott Crosson & Christopher Liese, 2015. "Nowcasting Intraseasonal Recreational Fishing Harvest with Internet Search Volume," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-18, September.
    8. David H Chae & Sean Clouston & Mark L Hatzenbuehler & Michael R Kramer & Hannah L F Cooper & Sacoby M Wilson & Seth I Stephens-Davidowitz & Robert S Gold & Bruce G Link, 2015. "Association between an Internet-Based Measure of Area Racism and Black Mortality," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-12, April.
    9. Eunae Yoo & Elliot Rabinovich & Bin Gu, 2020. "The Growth of Follower Networks on Social Media Platforms for Humanitarian Operations," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2696-2715, December.
    10. C. Douglas Swearingen & Joseph T. Ripberger, 2014. "Google Insights and U.S. Senate Elections: Does Search Traffic Provide a Valid Measure of Public Attention to Political Candidates?," Social Science Quarterly, Southwestern Social Science Association, vol. 95(3), pages 882-893, September.
    11. Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
    12. Ishani Chaudhuri & Parthajit Kayal, 2022. "Predicting Power of Ticker Search Volume in Indian Stock Market," Working Papers 2022-214, Madras School of Economics,Chennai,India.
    13. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    14. Sansone, Dario, 2019. "Pink work: Same-sex marriage, employment and discrimination," Journal of Public Economics, Elsevier, vol. 180(C).
    15. Pulkit Sharma & Achut Manandhar & Patrick Thomson & Jacob Katuva & Robert Hope & David A. Clifton, 2019. "Combining Multi-Modal Statistics for Welfare Prediction Using Deep Learning," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    16. Rameshwar Dubey & Nezih Altay & Constantin Blome, 2019. "Swift trust and commitment: The missing links for humanitarian supply chain coordination?," Annals of Operations Research, Springer, vol. 283(1), pages 159-177, December.
    17. John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353, arXiv.org.
    18. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
    19. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    20. Firas Rifai, 2018. "Transfer of Knowhow and Experiences from Commercial Logistics into Humanitarian Logistics to Improve Rescue Missions in Disaster Areas," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 8(3), pages 1-63, August.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00914-7. 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: https://www.nature.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.