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Targeting Influential Nodes for Recovery in Bootstrap Percolation on Hyperbolic Networks

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Network Intelligence Meets User Centered Social Media Networks (ENIC 2017)

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Abstract

The influence of our peers is a powerful reinforcement for our social behaviour, evidenced in voter behaviour and trend adoption. Bootstrap percolation is a simple method for modelling this process. In this work we look at bootstrap percolation on hyperbolic random geometric graphs, which have been used to model the Internet graph, and introduce a form of bootstrap percolation with recovery, showing that random targeting of nodes for recovery will delay adoption, but this effect is enhanced when nodes of high degree are selectively targeted.

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Authors and Affiliations

  1. Discipline of Information Technology, National University of Ireland, Galway, Ireland

    Christine Marshall & Colm O’Riordan

  2. School of Mathematics, National University of Ireland, Galway, Ireland

    James Cruickshank

Authors
  1. Christine Marshall
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  2. Colm O’Riordan
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  3. James Cruickshank
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Corresponding author

Correspondence to Christine Marshall .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. Department of Computer Science and Applied Cognitive Science, University of Duisburg-Essen, Duisburg, Nordrhein-Westfalen, Germany

    H. Ulrich Hoppe

  3. Computer Science and Applied Cognitive Science, University of Duisburg-Essen, Duisburg, Nordrhein-Westfalen, Germany

    Tobias Hecking

  4. Department of Computational Intelligence The Engine Centre, Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland

    Piotr Bródka

  5. Faculty of Computer Science and Management The Engine Centre, Wroclaw University of Science and Technology, Wroclaw, Poland

    Przemyslaw Kazienko

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Marshall, C., O’Riordan, C., Cruickshank, J. (2018). Targeting Influential Nodes for Recovery in Bootstrap Percolation on Hyperbolic Networks. In: Alhajj, R., Hoppe, H., Hecking, T., Bródka, P., Kazienko, P. (eds) Network Intelligence Meets User Centered Social Media Networks. ENIC 2017. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-90312-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-90312-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90311-8

  • Online ISBN: 978-3-319-90312-5

  • eBook Packages: Social SciencesSocial Sciences (R0)

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