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International Conference on Complex Networks and Their Applications

COMPLEX NETWORKS 2020 2020: Complex Networks & Their Applications IX pp 382–394Cite as

Influence Maximization for Dynamic Allocation in Voter Dynamics

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 943))

Abstract

In this paper, we study the competition between external controllers with fixed campaign budget in which one of the controllers attempts to maximize the share of a desired opinion in a group of agents who exchange opinions on a social network subject to voting dynamics. In contrast to allocating all the budget at the beginning of the campaign, we consider a version of a temporal influence maximization problem, where the controller has the flexibility to determine when to start control. We then explore the dependence of optimal starting times to achieve maximum vote shares at a finite time horizon on network heterogeneity. We find that, for short time horizons, maximum influence is achieved by starting relatively later on more heterogeneous networks than in less homogeneous networks, while the opposite holds for long time horizons.

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Author information

Authors and Affiliations

  1. School of Electronics and Computer Science, University of Southampton, Southampton, UK

    Zhongqi Cai, Markus Brede & Enrico Gerding

Authors
  1. Zhongqi Cai
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  2. Markus Brede
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  3. Enrico Gerding
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Corresponding author

Correspondence to Zhongqi Cai .

Editor information

Editors and Affiliations

  1. Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Madrid, Madrid, Spain

    Rosa M. Benito

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LIB, UFR Sciences et Techniques, Université de Bourgogne, Dijon, France

    Hocine Cherifi

  4. Grupo Interdisciplinar de Sistemas Complejos, Departamento de Matematicas, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Esteban Moro

  5. Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Luis Mateus Rocha

  6. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Marta Sales-Pardo

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Cai, Z., Brede, M., Gerding, E. (2021). Influence Maximization for Dynamic Allocation in Voter Dynamics. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 943. Springer, Cham. https://doi.org/10.1007/978-3-030-65347-7_32

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  • DOI: https://doi.org/10.1007/978-3-030-65347-7_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65346-0

  • Online ISBN: 978-3-030-65347-7

  • eBook Packages: EngineeringEngineering (R0)

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