• DocumentCode
    65767
  • Title

    Conjoining Speeds up Information Diffusion in Overlaying Social-Physical Networks

  • Author

    Yagan, Osman ; Dajun Qian ; Junshan Zhang ; Cochran, Douglas

  • Author_Institution
    CyLab, Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    31
  • Issue
    6
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    1038
  • Lastpage
    1048
  • Abstract
    We study the diffusion of information in an overlaying social-physical network. Specifically, we consider the following set-up: There is a physical information network where information spreads amongst people through conventional communication media (e.g., face-to-face communication, phone calls), and conjoint to this physical network, there are online social networks where information spreads via web sites such as Facebook, Twitter, FriendFeed, YouTube, etc. We quantify the size and the critical threshold of information epidemics in this conjoint social-physical network by assuming that information diffuses according to the SIR epidemic model. One interesting finding is that even if there is no percolation in the individual networks, percolation (i.e., information epidemics) can take place in the conjoint social-physical network. We also show, both analytically and experimentally, that the fraction of individuals who receive an item of information (started from an arbitrary node) is significantly larger in the conjoint social-physical network case, as compared to the case where the networks are disjoint. These findings reveal that conjoining the physical network with online social networks can have a dramatic impact on the speed and scale of information diffusion.
  • Keywords
    information dissemination; social networking (online); Facebook; FriendFeed; SIR epidemic model; Twitter; Web site; YouTube; communication media; conjoint social-physical network; face-to-face communication; information diffusion; information epidemics; information spread; online social network; overlaying social-physical network; phone call; physical information network; Coupled Social Networks; Information Diffusion; Percolation Theory; Random Graphs;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2013.130606
  • Filename
    6517108