Wanyun Shao, Ph.D
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Our new paper on global interest in earthquakes

9/27/2021

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    Our paper entitled "Data-driven modeling reveals the Western dominance of global pubic interest in earthquakes" has been published in Humanities and Social Sciences Communications (Nature Springer journal). Below please find the 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 hints 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."


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Fig. 1. Discrepancy between the top 10 deadliest and most recognized earthquakes since 2004: casualties (a) and initial global search activity volumes (GSAVs; (b)) of the 17 identified earthquakes. The size of circles in (a) and (b) represents the corresponding earthquake’s casualties and initial GSAVs. Black dots depict earthquakes in both categories (deadliest and most recognized). Blue and red dots depict the remainder of the deadliest and most recognized earthquakes, respectively. Areas colored in ivory depict the 62 nations that contribute to the daily GSAV data (Source: Kam et al. in press)
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Fig. 2. Consistency between Google Trends and Wikipedia pageview data. Time series of daily GSAVs (a) and daily views of the Wikipedia “Earthquake” webpage (b) from July 2015– August 2019, which was retrieved on January 1, 2020. (Source: Kam et al. in press)
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    Wanyun Shao, Ph.D

    I am a geographer who studies risk decision making within a geographic context.

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