Supporting crisis management via sub-event detection in social networks

This source preferred by Hamid Bouchachia

This data was imported from DBLP:

Authors: Pohl, D., Bouchachia, A. and Hellwagner, H.

Editors: Reddy, S. and Drira, K.

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6269211

Journal: WETICE

Pages: 373-378

Publisher: IEEE Computer Society

ISBN: 978-1-4673-1888-4

DOI: 10.1109/WETICE.2012.58

This data was imported from Scopus:

Authors: Pohl, D., Bouchachia, A. and Hellwagner, H.

Journal: Proceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE

Pages: 373-378

ISBN: 9780769547176

ISSN: 1524-4547

DOI: 10.1109/WETICE.2012.58

Social networks give the opportunity to gather and share knowledge about a situation of relevance. This so called user-generated content is getting increasingly important during crisis management. It facilitates the collaboration with citizens or parties involved from the very beginning of the crisis. The information captured in form of images, text or videos is a valuable source of identifying sub-events of a crisis. In this study, we use metadata of images and videos collected from Flickr and YouTube to extract sub-events in crisis situations. We investigate the suitability of clustering techniques to detect sub-events. In particular two algorithms are evaluated on several data sets related to crisis situations. The results show the high potential of the approach proposed. © 2012 IEEE.

The data on this page was last updated at 04:45 on September 21, 2017.