A Dynamic Model for On-Line Social Networks

  • Anthony Bonato
  • Noor Hadi
  • Paul Horn
  • Paweł Prałat
  • Changping Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5427)

Abstract

We present a deterministic model for on-line social networks based on transitivity and local knowledge in social interactions. In the Iterated Local Transitivity (ILT) model, at each time-step and for every existing node x, a new node appears which joins to the closed neighbour set of x. The ILT model provably satisfies a number of both local and global properties that were observed in real-world on-line social and other complex networks, such as a densification power law, decreasing average distance, and higher clustering than in random graphs with the same average degree. Experimental studies of social networks demonstrate poor expansion properties as a consequence of the existence of communities with low number of inter-community links. A spectral gap for both the adjacency and normalized Laplacian matrices is proved for graphs arising from the ILT model, thereby simulating such bad expansion properties.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Anthony Bonato
    • 1
  • Noor Hadi
    • 2
  • Paul Horn
    • 3
  • Paweł Prałat
    • 4
  • Changping Wang
    • 1
  1. 1.Ryerson UniversityTorontoCanada
  2. 2.Wilfrid Laurier UniversityWaterlooCanada
  3. 3.University of CaliforniaSan DiegoUSA
  4. 4.Dalhousie UniversityHalifaxCanada

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