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Modeling Social Networks through User Background and Behavior

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Algorithms and Models for the Web Graph (WAW 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6732))

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Abstract

We propose a generative model for social networks, both undirected and directed, that takes into account two fundamental characteristics of the user: background (specifically, the real world groups to which the user belongs); and behavior (namely, the ways in which the user engages in surfing activity and occasionally adds links to other users encountered this way). Our experiments show that networks generated by our model compare very well with data from a host of actual social networks with respect to a battery of standard metrics such as degree distribution and assortativity, and verify well known predictions about social networks such as densification and shrinking diameter. We also propose a new metric for social networks intended to gauge the level of surfing activity, namely the correlation between degree and Page rank.

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Author information

Authors and Affiliations

  1. Georgia Institute of Technology, USA

    Ilias Foudalis

  2. Microsoft Research, Redmond

    Kamal Jain

  3. EECS Department, UC, Berkeley

    Christos Papadimitriou

  4. Department of Informatics, Athens University of Economics and Business, Greece

    Martha Sideri

Authors
  1. Ilias Foudalis
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  2. Kamal Jain
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  3. Christos Papadimitriou
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  4. Martha Sideri
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Editor information

Editors and Affiliations

  1. Department of Mathematical Sciences, Carnegie Mellon University, 15213, Pittsburgh, PA, USA

    Alan Frieze

  2. Department of Mathematics and Computer Science, Emory University, 400 Dowman Drive, W401, 30322, Atlanta, GA, USA

    Paul Horn

  3. Department of Mathematics, West Virginia University, 26506-6310, Morgantown, WV, USA

    Paweł Prałat

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© 2011 Springer-Verlag Berlin Heidelberg

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Foudalis, I., Jain, K., Papadimitriou, C., Sideri, M. (2011). Modeling Social Networks through User Background and Behavior. In: Frieze, A., Horn, P., Prałat, P. (eds) Algorithms and Models for the Web Graph. WAW 2011. Lecture Notes in Computer Science, vol 6732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21286-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-21286-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21285-7

  • Online ISBN: 978-3-642-21286-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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