Issue No. 02 - Mar.-Apr. (2014 vol. 29)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2013.126
Stuart E. Middleton , University of Southampton IT Innovation Centre
Lee Middleton , University of Southampton IT Innovation Centre
Stefano Modafferi , University of Southampton IT Innovation Centre
The proposed social media crisis mapping platform for natural disasters uses locations from gazetteer, street map, and volunteered geographic information (VGI) sources for areas at risk of disaster and matches them to geoparsed real-time tweet data streams. The authors use statistical analysis to generate real-time crisis maps. Geoparsing results are benchmarked against existing published work and evaluated across multilingual datasets. Two case studies compare five-day tweet crisis maps to official post-event impact assessment from the US National Geospatial Agency (NGA), compiled from verified satellite and aerial imagery sources.
Real-time systems, Floods, Databases, Media, Geospatial analysis, Twitter, Earthquakes,crisis management, Real-time systems, Floods, Databases, Media, Geospatial analysis, Twitter, Earthquakes, intelligent systems, geoparsing, crisis mapping, natural language processing, NLP, volunteered geographic information, VGI, natural disaster
Stuart E. Middleton, Lee Middleton, Stefano Modafferi, "Real-Time Crisis Mapping of Natural Disasters Using Social Media", IEEE Intelligent Systems, vol. 29, no. , pp. 9-17, Mar.-Apr. 2014, doi:10.1109/MIS.2013.126