• DocumentCode
    3742975
  • Title

    Strategy for processing and analyzing social media data streams in emergencies

  • Author

    Matthias Moi;Therese Friberg;Robin Marterer;Christian Reuter;Thomas Ludwig;Deborah Markham;Mike Hewlett;Andrew Muddiman

  • Author_Institution
    C.I.K., University of Paderborn, Germany
  • fYear
    2015
  • Firstpage
    42
  • Lastpage
    48
  • Abstract
    People are using social media to a greater extent, particularly in emergency situations. However, approaches for processing and analyzing the vast quantities of data produced currently lag far behind. In this paper we discuss important steps, and the associated challenges, for processing and analyzing social media in emergencies. In our research project EmerGent, a huge volume of low-quality messages will be continuously gathered from a variety of social media services such as Facebook or Twitter. Our aim is to design a software system that will process and analyze social media data, transforming the high volume of noisy data into a low volume of rich content that is useful to emergency personnel. Therefore, suitable techniques are needed to extract and condense key information from raw social media data, allowing detection of relevant events and generation of alerts pertinent to emergency personnel.
  • Keywords
    "Data mining","Media","Emergency services","Ontologies","Semantics","Facebook","Twitter"
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies for Disaster Management (ICT-DM), 2015 2nd International Conference on
  • Type

    conf

  • DOI
    10.1109/ICT-DM.2015.7402055
  • Filename
    7402055