Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Conference papers

Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets

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.
Document type :
Conference papers
Complete list of metadata

Cited literature [17 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Wednesday, January 3, 2018 - 5:20:47 PM
Last modification on : Wednesday, April 6, 2022 - 5:14:03 PM
Long-term archiving on: : Thursday, May 3, 2018 - 8:31:04 AM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Aurelie Montarnal, Shane Halse, Andrea Tapia, Sébastien Truptil, Frederick Benaben. Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets. 18th Working Conference on Virtual Enterprises (PROVE), Sep 2017, Vicenza, Italy. pp.658-665, ⟨10.1007/978-3-319-65151-4_58⟩. ⟨hal-01674873⟩



Record views


Files downloads