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Convergence in (Social) Influence Networks

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Distributed Computing (DISC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8205))

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Abstract

We study the convergence of influence networks, where each node changes its state according to the majority of its neighbors. Our main result is a new Ω(n 2/log2 n) bound on the convergence time in the synchronous model, solving the classic “Democrats and Republicans” problem. Furthermore, we give a bound of Θ(n 2) for the sequential model in which the sequence of steps is given by an adversary and a bound of Θ(n) for the sequential model in which the sequence of steps is given by a benevolent process.

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Author information

Authors and Affiliations

  1. Computer Engineering and Networks Laboratory (TIK), ETH Zürich, Switzerland

    Silvio Frischknecht, Barbara Keller & Roger Wattenhofer

Authors
  1. Silvio Frischknecht
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  2. Barbara Keller
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  3. Roger Wattenhofer
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Editor information

Editors and Affiliations

  1. Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel-Aviv, Israel

    Yehuda Afek

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Frischknecht, S., Keller, B., Wattenhofer, R. (2013). Convergence in (Social) Influence Networks. In: Afek, Y. (eds) Distributed Computing. DISC 2013. Lecture Notes in Computer Science, vol 8205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41527-2_30

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  • DOI: https://doi.org/10.1007/978-3-642-41527-2_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41526-5

  • Online ISBN: 978-3-642-41527-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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