Social Media represent today the way used by millions of users to interact according to new paradigms of communication and participation: users are then an ideal ground for the study of the diffusion of new topics of discussion and new dynamics of communication.
Social Media platforms can be used as starting point for Social Sensing applications in which users can be considered as providers of information. 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 the Emergency Management.
This field is interesting for a variety of stakeholders: government agencies, industry information, ordinary citizens. Using the SM for Emergency Management, these subjects can gather updated information on emerging situations of danger, in order to gain greater situational awareness, the possibility of alerting interested parties promptly or verify information obtained through other channels. A system able to predict or identify events that are of social concern can be referred as an Early Warning system.
In this work we propose a general architecture for an Early Warning system and, as a proofofconcept we describe an implementation of this architecture for a real scenario.
We use Twitter as source of information for the detection of earthquakes in the Italian territory.
We compare our results with official data provided by the National Institute of Geophysics and Volcanology (INGV), the authority responsible of the monitoring of seismic events in Italy. Results show an high ability of the system in the identification of events with intensity equal or greater than 3.5th degree on the Richter scale with 10% of False Positives.