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 language | English (US) |
|---|---|
| Title of host publication | IFIP Advances in Information and Communication Technology |
| Editors | Hamideh Afsarmanesh, Rosanna Fornasiero, Luis M. Camarinha-Matos |
| Publisher | Springer New York LLC |
| Pages | 658-665 |
| Number of pages | 8 |
| ISBN (Print) | 9783319651507 |
| DOIs | |
| State | Published - Jan 1 2017 |
| Event | 18th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2017 - Vicenza, Italy Duration: Sep 18 2017 → Sep 20 2017 |
Publication series
| Name | IFIP Advances in Information and Communication Technology |
|---|---|
| Volume | 506 |
| ISSN (Print) | 1868-4238 |
Other
| Other | 18th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2017 |
|---|---|
| Country | Italy |
| City | Vicenza |
| Period | 9/18/17 → 9/20/17 |
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All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Networks and Communications
- Information Systems and Management
Cite this
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Automated emergence of a crisis situation model in crisis response based on tweets. / Montarnal, Aurélie; Halse, Shane; Tapia, Andrea; Truptil, Sébastien; Benaben, Frederick.
IFIP Advances in Information and Communication Technology. ed. / Hamideh Afsarmanesh; Rosanna Fornasiero; Luis M. Camarinha-Matos. Springer New York LLC, 2017. p. 658-665 (IFIP Advances in Information and Communication Technology; Vol. 506).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Automated emergence of a crisis situation model in crisis response based on tweets
AU - Montarnal, Aurélie
AU - Halse, Shane
AU - Tapia, Andrea
AU - Truptil, Sébastien
AU - Benaben, Frederick
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85029603498&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85029603498&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-65151-4_58
DO - 10.1007/978-3-319-65151-4_58
M3 - Conference contribution
AN - SCOPUS:85029603498
SN - 9783319651507
T3 - IFIP Advances in Information and Communication Technology
SP - 658
EP - 665
BT - IFIP Advances in Information and Communication Technology
A2 - Afsarmanesh, Hamideh
A2 - Fornasiero, Rosanna
A2 - Camarinha-Matos, Luis M.
PB - Springer New York LLC
ER -