Supporting Crisis Management via Detection of Sub-Events in Social Networks

Abstract

Social networks provide the opportunity to gather and share knowledge about a situation of relevance. User-generated content is getting increasingly important during crisis management. It facilitates the collaboration with citizens or involved parties from the very beginning of the crisis. The information captured in the form of images, text or videos is a valuable source of identifying sub-events of a crisis. In this study, the authors use metadata of images and videos collected from Flickr and YouTube to extract crisis sub-events. The authors 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 proposed approach. In addition, the authors validate the idea of sub-event detection for the authors’ future research based on a survey conducted among practitioners. Their responses show the potential of using social media in combination with sub-event detection during emergency management.