Natural disasters have been a major cause of huge losses for both people’s life and property. There is no doubt that the importance of Emergency Warning System (EWS) has been considered more seriously than ever. Unfortunately, most EWSs do not provide acceptable service to identify people who might be affected by a certain disasters. In this project, we propose an approach to identify possibly affected users of a target disaster by using online social networks. The proposed method consists of three phases. First of all, we collect location information from social network websites, such as Twitter. Then, we propose a social network analysis algorithm to identify potential victims and communities. Finally, we conduct an experiment to test the accuracy and efficiency of the approach. Based on the result, we claim that the approach can facilitate identifying potential victims effectively based on data from social networking systems.
History
Publication title
Software Engineering, Business Continuity, and Education - Proceedings of the 2011 International Conference on Advanced Software Engineering and Its Applications (ASEA 2011)
Volume
257
Editors
TH Kim, H Adeli, HK Kim, HJ Kang, KJ Kim, A Kiumi, BH Kang
Pagination
541-550
ISBN
978-3-642-27207-3
Department/School
School of Information and Communication Technology
Publisher
Springer- Verlag
Place of publication
Berlin Heidelberg
Event title
2011 International Conference on Advanced Software Engineering and Its Applications (ASEA 2011)
Event Venue
Jeju Island, Korea
Date of Event (Start Date)
2011-12-08
Date of Event (End Date)
2011-12-10
Rights statement
Copyright 2011 Springer-Verlag
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified