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Zombie politics: evolutionary algorithms to counteract the spread of negative opinions

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Abstract

This paper is about simulating the spread of opinions in a society and about finding ways to counteract that spread. To abstract away from potentially emotionally laden opinions, we instead simulate the spread of a zombie outbreak in a society. The virus causing this outbreak is different from traditional approaches: It not only causes a binary outcome (healthy vs. infected) but rather a continuous outcome. To counteract the outbreak, a discrete number of infection-level-specific treatments are available. This corresponds to acts of mild persuasion or the threats of legal action in the opinion spreading use case. This paper offers a genetic and a cultural algorithm that find the optimal mixture of treatments during the run of the simulation. They are assessed in a number of different scenarios. It is shown that albeit far from being perfect, the cultural algorithm delivers superior performance at lower computational expense.

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Notes

  1. A noteworthy exemption are perhaps the Verbotsgesetze enacted in Austria and Germany under the impression of denazification. Here, indeed, prominent advocates of especially despicable opinions, are being held in prison and thus effectively removed from the population.

  2. All computations were done in R (R Core Team 2012); plots were produced using ggplot2 (Wickham 2009).

  3. or a small number of.

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Authors and Affiliations

  1. Department of Business and Management, Webster Vienna Private University, Praterstraße 23, 1020, Vienna, Austria

    Ronald Hochreiter

  2. Raiffeisen Bank International AG, Am Stadtpark 9, 1030, Vienna, Austria

    Christoph Waldhauser

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  1. Ronald Hochreiter
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  2. Christoph Waldhauser
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Correspondence to Ronald Hochreiter.

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Communicated by V. Loia.

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Hochreiter, R., Waldhauser, C. Zombie politics: evolutionary algorithms to counteract the spread of negative opinions. Soft Comput 24, 591–601 (2020). https://doi.org/10.1007/s00500-019-04251-5

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