Contributo in atti di convegno, 2015, ENG

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

S. Cresci(1); A. Cimino (1); F. Dell'Orletta (2); M. Tesconi (1)

CNR-IIT, Pisa, Italy (1); CNR-ILC, Pisa, Italy (2)

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, pp. 1–8, Miami, USA, 02/11/2015

Keywords

crisis informatics, Emergency Management, geoparsing, social media mining, Twitter

CNR authors

Cimino Andrea, Cresci Stefano, Tesconi Maurizio, Dell Orletta Felice

CNR institutes

IIT – Istituto di informatica e telematica, ILC – Istituto di linguistica computazionale "Antonio Zampolli"

ID: 337237

Year: 2015

Type: Contributo in atti di convegno

Creation: 2015-11-10 15:45:59.000

Last update: 2023-11-06 19:33:08.000

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:337237