• 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