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.
Highlights
Natural, man-made and technological disasters present a constant threat to society [1]
To evaluate performance of the sensor method, we focus on the entry time t, defined as the time a user first appears in our dataset by posting a message relevant to Hurricane Sandy
Let us define the lead-time as the difference between the average entry times of the sensor group and its corresponding control group:Dt 1⁄4 htSi À htCi, with negative lead-times indicating awareness advantage
Summary
Man-made and technological disasters present a constant threat to society [1]. To address this central question, we study performance of the sensor method during Hurricane Sandy to establish if there is an early awareness advantage, what is its magnitude, and what is the effect of geographical location of users.
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