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Crisis Mapping during Natural Disasters via Text Analysis of Social Media Messages

Recent disasters demonstrated the central role of social media during emergencies thus motivating the exploitation of such data for crisis mapping. We propose a crisis mapping system that addresses limitations of current state-of-the-art approaches by analyzing the textual content of disaster reports from a twofold perspective. A damage detection component employs a SVM classifier to detect mentions of damage among emergency reports. A novel geoparsing technique is proposed and used to perform message geolocation. We report on a case study to show how the information extracted through damage detection and message geolocation can be combined to produce accurate crisis maps. Our crisis maps clearly detect both highly and lightly damaged areas, thus opening up the possibility to prioritize rescue efforts where they are most needed.


Web Information Systems Engineering–WISE 2015, Miami, USA, 2015

Autori esterni: Andrea Cimino (ILC-CNR), Felice Dell'Orletta (ILC-CNR)
Autori IIT:

Tipo: Articolo in Atti di convegno internazionale con referee
Area di disciplina: Information Technology and Communication Systems

File: Cresci, 2015, Crisis Mapping during Natural Disasters via Text Analysis of Social Media Messages.pdf

Attività: Social Media Analysis