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.
National Information and Communications Technology Australia, Melbourne, Victoria, Australia;National Information and Communications Technology Australia, Melbourne, Victoria, Australia;Department of Mathematics & GISC, Universidad Carlos III de Madrid, Leganés, Spain;Instituto de Ingeniería del Conocimiento, Universidad Autónoma de Madrid, Madrid, Spain;National Information and Communications Technology Australia, Melbourne, Victoria, Australia;Research School of Computer Science, Australian National University, Canberra, Australian Capital Territory, Australia;National Information and Communications Technology Australia, Melbourne, Victoria, Australia;Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, United States of America
Recommended Citation:
Yury Kryvasheyeu,Haohui Chen,Esteban Moro,et al. Performance of Social Network Sensors during Hurricane Sandy[J]. PLOS ONE,2015-01-01,10(2)