Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 |
| Seiten | 1305-1308 |
| Seitenumfang | 4 |
| ISBN (elektronisch) | 9781450356572 |
| Publikationsstatus | Veröffentlicht - 27 Juni 2018 |
| Veranstaltung | 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 - Ann Arbor, USA / Vereinigte Staaten Dauer: 8 Juli 2018 → 12 Juli 2018 |
Abstract
The observation of social media provides an important complementing source of information about an unfolding event such as a crisis situation. For this purpose we have developed and demonstrate Sover!, a system to monitor real-time dynamic events via Twitter targeting the needs of aid organizations. At its core it builds upon an effective adaptive crawler, which combines two social media streams in a Bayesian inference framework and after each time-window updates the probabilities of whether given keywords are relevant for an event. Sover! also exposes the crawling functionality so a user can actively influence the evolving selection of keywords. The crawling activity feeds a rich dashboard, which enables the user to get a better understanding of a crisis situation as it unfolds in real-time.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Informatik (insg.)
- Computergrafik und computergestütztes Design
- Informatik (insg.)
- Information systems
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. 2018. S. 1305-1308.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Sover! Social media observer
AU - Hadgu, Asmelash Teka
AU - Abualhaija, Sallam
AU - Niederée, Claudia
N1 - Publisher Copyright: © 2018 Authors. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/6/27
Y1 - 2018/6/27
N2 - The observation of social media provides an important complementing source of information about an unfolding event such as a crisis situation. For this purpose we have developed and demonstrate Sover!, a system to monitor real-time dynamic events via Twitter targeting the needs of aid organizations. At its core it builds upon an effective adaptive crawler, which combines two social media streams in a Bayesian inference framework and after each time-window updates the probabilities of whether given keywords are relevant for an event. Sover! also exposes the crawling functionality so a user can actively influence the evolving selection of keywords. The crawling activity feeds a rich dashboard, which enables the user to get a better understanding of a crisis situation as it unfolds in real-time.
AB - The observation of social media provides an important complementing source of information about an unfolding event such as a crisis situation. For this purpose we have developed and demonstrate Sover!, a system to monitor real-time dynamic events via Twitter targeting the needs of aid organizations. At its core it builds upon an effective adaptive crawler, which combines two social media streams in a Bayesian inference framework and after each time-window updates the probabilities of whether given keywords are relevant for an event. Sover! also exposes the crawling functionality so a user can actively influence the evolving selection of keywords. The crawling activity feeds a rich dashboard, which enables the user to get a better understanding of a crisis situation as it unfolds in real-time.
KW - Crisis management
KW - Real-time adaptive search
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85051512870&partnerID=8YFLogxK
U2 - 10.1145/3209978.3210173
DO - 10.1145/3209978.3210173
M3 - Conference contribution
AN - SCOPUS:85051512870
SP - 1305
EP - 1308
BT - 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
T2 - 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
Y2 - 8 July 2018 through 12 July 2018
ER -