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Extending DeGroot Opinion Formation for Signed Graphs and Minimizing Polarization

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Complex Networks & Their Applications IX (COMPLEX NETWORKS 2020 2020)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 944))

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Abstract

Signed graphs offer a more rich representation of social networks than unsigned graphs. Most opinion formation models are developed for unsigned graphs. In this paper, we extend DeGrootian opinion dynamics to accommodate signed graphs. Furthermore, we also define the task of minimizing polarization on a budget through the lens of this DeGrootian model as an optimization problem and provide numerical results to demonstrate a decrease in polarization.

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Notes

  1. 1.

    https://julialang.org/.

  2. 2.

    https://github.com/InzamamRahaman/SignedDegroot.

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Authors and Affiliations

  1. The University of the West Indies, St. Augustine, Trinidad and Tobago

    Inzamam Rahaman & Patrick Hosein

Authors
  1. Inzamam Rahaman
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  2. Patrick Hosein
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Corresponding author

Correspondence to Inzamam Rahaman .

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. LE2I, 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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Rahaman, I., Hosein, P. (2021). Extending DeGroot Opinion Formation for Signed Graphs and Minimizing Polarization. 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 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_24

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  • DOI: https://doi.org/10.1007/978-3-030-65351-4_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65350-7

  • Online ISBN: 978-3-030-65351-4

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