DocumentCode :
119667
Title :
Real-time identification and monitoring of abnormal events based on microblog and emergency call data using SMART
Author :
Zhang, Jiawei ; Afzal, Shehzad ; Breunig, Dallas ; Xia, Jing ; Zhao, Jieqiong ; Sheeley, Isaac ; Christopher, Joseph ; Ebert, David S. ; Guo, Chen ; Xu, Shang ; Yu, Jim ; Wang, Qiaoying ; Wang, Chen ; Qian, Zhenyu ; Chen, Yingjie
Author_Institution :
Purdue University in West Lafayette, IN, USA
fYear :
2014
fDate :
25-31 Oct. 2014
Firstpage :
393
Lastpage :
394
Abstract :
This article describes a real-time visual analytics process based on microblog and emergency call data to solve VAST 2014 Mini Challenge 3. We extended SMART system (Social Media Analytics and Reporting Toolkit), developed by the U.S. Department of Homeland Security´s VACCINE Center. Our system consists of multiple linked views to allow the analyst monitor topic evolution, identify influential microblog users, observe geo-location patterns and examine correlations among different data sources. Extensions to our previous work include a time series view, a reply/retweet networks view, and integration of emergency call data.
Keywords :
Microblog; Multiple Linked Views; Spatiotemporal Analysis; Visual Analytics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
Conference_Location :
Paris, France
Type :
conf
DOI :
10.1109/VAST.2014.7042582
Filename :
7042582
Link To Document :
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