TwiFelt: real-time mapping of earthquake perception areas through the analysis of Twitter streams
Sponsors
Istituto Nazionale di Geofisica e Vulcanologia
Language
English
Obiettivo Specifico
4T. Fisica dei terremoti e scenari cosismici
5T. Sorveglianza sismica e operatività post-terremoto
1IT. Reti di monitoraggio e Osservazioni
Status
Published
Peer review journal
Yes
Date Issued
2013
Series/Report No.
Rapporti Tecnici INGV
254
Subjects
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.
Type
report
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