Longitudal Analysis and Modeling of Large-Scale Social Networks

The data generated by digital communication technologies will be used to:

  1. Test/validate existing social network theories about the mechanisms underlying network dynamics by developing quantitative high-fidelity temporal stochastic models of human behavior within social networks.
  2. Produce a data-driven, dynamic network modeling suite with prediction capabilities.


Collaborators

  • Dr. Mark Alber (ACMS, Notre Dame)
  • Dr. Zoltán Toroczkai (Physics, Notre Dame)
  • Dr. Nitesh Chawla (Computer Science and Engineering, Notre Dame)
  • Drs. Omar Lizardo and David Hachen (Sociology, Notre Dame)
  • Notre Dame graduate students: Tanya Salyers (ACMS), Anthony Strathman (Physics), Ryan Lichtenwalter (Computer Science and Engineering), and Cheng Wang (Sociology)
  • Dr. Albert-László Barabasi (Physics, Northeastern University)
  • Hyunju Kim, (Postdoc, Physics, Virginia Tech)

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