Abstract

Social Sensing is based on the idea that communities or groups of people provide a set of information similar to those obtainable from a single sensor. This amount of information generate a complex and adequate knowledge of one or more specific issues. A possible field of application for Social Sensing is Emergency Management. By using the Social Media it is possible to gather updated information about emerging situations of danger, in order to gain greater situational awareness and to alert interested parties promptly or verify information obtained through other channels. A system able to timely detect events that are of social concern can be referred to as an Early Warning system. In this work we propose a novel and general architecture for an early warning system and, as a proof-of-concept, we describe an implementation of this architecture for a real scenario. We use Twitter as source of information for the detection of earthquakes on the Italian territory. We compare our results with official data provided by the National Institute of Geophysics and Volcanology, the authority responsible for the monitoring of seismic events in Italy. Results show an high ability of the system in the timely detection of events with magnitude equal or greater than 3.5 Richter with only 10% of False Positives.

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