TwiFelt: real-time mapping of earthquake perception areas through the analysis of Twitter streams

Abstract

Twitter is one of the most used social networks and its specific features makes it well suited for the real-time analysis of geographic trends of a specific topic. Earle et al. (2011) have shown how the analysis of Twitter streams can provide a useful tool for the early detection of earthquakes at a global scale. They proved that data mining of social networks could provide useful information in Seismology. Here we present a software system named TwiFelt, aimed at providing real-time earthquake perception maps from the analysis of Twitter streams. The system is based on the collection of geotagged tweets (i.e. tweets having a geographic reference) containing selected keywords, its statistical interpretation and its interactive graphical representation.