• DocumentCode
    497768
  • Title

    Estimation of adversarial social networks by fusion of information from a wide range of sources

  • Author

    Josephson, John R. ; Eckroth, Joshua ; Miller, Timothy N.

  • Author_Institution
    Comput. Sci. & Eng. Dept., Ohio State Univ., OH, USA
  • fYear
    2009
  • fDate
    6-9 July 2009
  • Firstpage
    2144
  • Lastpage
    2152
  • Abstract
    A data structure is described that serves to define a target structure for estimating social networks. It represents who knows whom, the strength and polarity of associations, and levels of confidence that linked individuals are actually personally acquainted. This network, which represents social structure, is embedded in a more inclusive network structure that also represents vehicles, places and organizations. This broader structure can be used to accumulate information to enable automated inferencing to assist human processing in estimating the social network of interest. How portions of this inferencing can be done is briefly described, and a scenario is given that illustrates the use of this kind of fused information to make a decision. We also review a range of hard and soft information sources with emerging value for estimating adversarial social networks, and describe how these sources can be used for the purpose.
  • Keywords
    data structures; social networking (online); adversarial social networks; data structure; information fusion; Biosensors; Computer displays; Data mining; Data structures; Humans; Information resources; Intelligent networks; Intelligent sensors; Social network services; State estimation; Information fusion; asymmetric warfare; biometrics; social networks; soft information; urban operations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2009. FUSION '09. 12th International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-0-9824-4380-4
  • Type

    conf

  • Filename
    5203862