Conjoining speeds up information diffusion in overlaying social-physical networks

Osman Yagan, Dajun Qian, Junshan Zhang, Douglas Cochran

Research output: Contribution to journalArticlepeer-review

103 Scopus citations

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.

Original languageEnglish (US)
Article number6517108
Pages (from-to)1038-1048
Number of pages11
JournalIEEE Journal on Selected Areas in Communications
Volume31
Issue number6
DOIs
StatePublished - 2013

Keywords

  • Coupled Social Networks
  • Information Diffusion
  • Percolation Theory
  • Random Graphs

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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