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Election Manipulation on Social Networks with Abstention

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Multi-Agent Systems (EUMAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14282))

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Abstract

The Election Manipulation through the diffusion of (fake) news on social networks has been a subject that recently attracted the interest of many works in both in the communities of AI and social choice theory. However, all these works assume that each voter has to express her vote, not considering the possibility that she could abstain. One of the reasons of this omission is the lack of a satisfying modeling of how people choose to abstain. In this work, we try to fill this gap by presenting an innovative model for abstention that will match most of the real-world observations about the topic. Next, we will provide experimental evidence that abstention opportunity will help the manipulator to control the elections, by comparing how well-known algorithms and heuristics behave in the setting with and without abstention.

*Supported by the Italian MIUR PRIN 2017 Project ALGADIMAR “Algorithms, Games, and Digital Markets” and by “GNCS-INdAM”.

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Notes

  1. 1.

    E.g., a cartoon with a text “Hillary Thinks African Americans are Super Predators” was planned to be delivered to certain African American voters through Facebook “dark posts” – non-public posts whose viewership is controlled by the campaign [24].

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Authors and Affiliations

  1. Università degli Studi di Salerno, 84084, Fisciano, SA, Italy

    Vincenzo Auletta, Diodato Ferraioli & Carmine Viscito

Authors
  1. Vincenzo Auletta
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  2. Diodato Ferraioli
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  3. Carmine Viscito
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Corresponding authors

Correspondence to Vincenzo Auletta or Diodato Ferraioli .

Editor information

Editors and Affiliations

  1. Télécom Paris, Paris, France

    Vadim Malvone

  2. Universitá degli Studi di Napoli Federico II, Naples, Italy

    Aniello Murano

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Auletta, V., Ferraioli, D., Viscito, C. (2023). Election Manipulation on Social Networks with Abstention. In: Malvone, V., Murano, A. (eds) Multi-Agent Systems. EUMAS 2023. Lecture Notes in Computer Science(), vol 14282. Springer, Cham. https://doi.org/10.1007/978-3-031-43264-4_29

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  • DOI: https://doi.org/10.1007/978-3-031-43264-4_29

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  • Online ISBN: 978-3-031-43264-4

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