• DocumentCode
    2135235
  • Title

    Monitor placement to timely detect misinformation in Online Social Networks

  • Author

    Zhang, Huiling ; Alim, Md Abdul ; Thai, My T. ; Nguyen, Hien T.

  • Author_Institution
    Department of Computer & Information Science & Engineering, University of Florida, Gainesville, 32611, United States
  • fYear
    2015
  • fDate
    8-12 June 2015
  • Firstpage
    1152
  • Lastpage
    1157
  • Abstract
    Online Social Networks (OSNs), such as Facebook, Twitter and Google+, facilitate the interactions and communications among people. However, they also make it a fertile land for misinformation to rapidly spread out, which may lead to detrimental consequences. Thus it is imperative to detect the misinformation propagating through OSNs by placing monitors. In this paper, we first study a general misinformation detection problem and show its equivalence to the influence maximization problem. Moreover, in order to prevent misinformation from reaching specific users, we define a τ-Monitor Placement problem for cases where the partial knowledge of misinformation sources is available. We prove the #P complexity of this problem and additionally propose an efficient algorithm to solve it. Extensive experiments on real-world data show the effectiveness of our proposed algorithm with respect to minimizing the number of monitors.
  • Keywords
    Complexity theory; Image edge detection; Integrated circuit modeling; Monitoring; Polynomials; Twitter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2015 IEEE International Conference on
  • Conference_Location
    London, United Kingdom
  • Type

    conf

  • DOI
    10.1109/ICC.2015.7248478
  • Filename
    7248478