Automated emergence of a crisis situation model in crisis response based on tweets

Aurélie Montarnal, Shane Halse, Andrea Tapia, Sébastien Truptil, Frederick Benaben

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

During a crisis, being able to understand quickly the situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the crisis situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize crisis situations. It is based on a specific metamodel that determines the different concepts required to model a crisis situation.

Original languageEnglish (US)
Title of host publicationIFIP Advances in Information and Communication Technology
EditorsHamideh Afsarmanesh, Rosanna Fornasiero, Luis M. Camarinha-Matos
PublisherSpringer New York LLC
Pages658-665
Number of pages8
ISBN (Print)9783319651507
DOIs
StatePublished - 2017
Event18th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2017 - Vicenza, Italy
Duration: Sep 18 2017Sep 20 2017

Publication series

NameIFIP Advances in Information and Communication Technology
Volume506
ISSN (Print)1868-4238

Other

Other18th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2017
CountryItaly
CityVicenza
Period9/18/179/20/17

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management

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