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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 |
Subject Classification: | 04. Solid Earth::04.06. Seismology::04.06.06. Surveys, measurements, and monitoring 05. General::05.03. Educational, History of Science, Public Issues::05.03.99. General or miscellaneous |
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: | Reports |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| 2013_Dauria.pdf | Main article | 905.97 kB | Adobe PDF | View/Open |
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