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Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9776

Authors: D'Auria, Luca*
Giudicepietro, Flora*
Title: TwiFelt: real-time mapping of earthquake perception areas through the analysis of Twitter streams
Issue Date: 2013
URL: http://istituto.ingv.it/l-ingv/produzione-scientifica/rapporti-tecnici-ingv/archivio/rapporti-tecnici-2013/2015-02-12.9649518743
Series/Report no.: Rapporti Tecnici INGV
254
Keywords: twitter
earthquake perception
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.
Appears in Collections:05.03.99. General or miscellaneous
04.06.06. Surveys, measurements, and monitoring
Reports

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