Performance of Social Network Sensors During Hurricane Sandy

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 a mean to derive early-warning sensors, improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioural 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 user's 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 significant role in determining the scale of such advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility of implementing a simple "sentiment sensing" technique to detect and locate disasters.

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Cited by in corpus (10)

• Social media usage patterns during natural hazards
• Tail-scope: Using friends to estimate heavy tails of degree distributions in large-scale complex networks
• Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data
• Mining social media data for biomedical signals and health-related behavior
• Understanding Information Spreading in Social Media during Hurricane Sandy: User Activity and Network Properties
• Generalized friendship paradox in networks with tunable degree-attribute correlation
• Identifying Crisis Response Communities in Online Social Networks for Compound Disasters: The Case of Hurricane Laura and Covid-19
• Evaluating stochastic seeding strategies in networks
• A Practical Guide for the Effective Evaluation of Twitter User Geolocation
• Nowcasting Disaster Damage