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Information flow during catastrophic events is a critical aspect of disastermanagement. Modern communication platforms, in particular online socialnetworks, provide an opportunity to study such flow, and a mean to deriveearly-warning sensors, improving emergency preparedness and response.Performance of the social networks sensor method, based on topological andbehavioural properties derived from the "friendship paradox", is studied herefor over 50 million Twitter messages posted before, during, and after HurricaneSandy. We find that differences in user's network centrality effectivelytranslate into moderate awareness advantage (up to 26 hours); and thatgeo-location of users within or outside of the hurricane-affected area playssignificant role in determining the scale of such advantage. Emotional responseappears to be universal regardless of the position in the network topology, anddisplays characteristic, easily detectable patterns, opening a possibility ofimplementing a simple "sentiment sensing" technique to detect and locatedisasters.

Performance of Social Network Sensors During Hurricane Sandy