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February 5, 20260 citations

Emergence of complexity in opinion propagation: A reaction-diffusion model

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RDRomain DucasseUniversidad Peruana de Ciencias e InformáticaSTSamuel TrétonCentre National de la Recherche Scientifique

Key Points

  • The aim is to analyze how opinions spread and accumulate in a population through a reaction-diffusion model.
  • Utilized a reaction-diffusion framework based on the classical SIR model.
  • Established rules for individual opinion adoption during interactions.
  • Characterized the maximal complexity of opinions that can persist and propagate.
  • Identified a maximal complexity of opinions that can emerge and spread.
  • Showed that maximal complexity grows almost exponentially with population size.
  • Demonstrated that model parameters significantly influence this complexity.

Abstract

We analyze a model designed to describe the spread and accumulation of opinions in a population. Inspired by the social contagion paradigm, our model is built on the classical SIR model of Kermack and McKendrick and consists in a system of reaction-diffusion equations. In the scenario we consider, individuals within the population can adopt new opinions via interactions with others, following some simple rules. The individuals can gradually adopt more complex opinions over time. Our main result is the characterization of a maximal complexity of opinions that can persist and propagate. In addition, we show how the parameters of the model influence this maximal complexity. Notably, we show that it grows almost exponentially with the size of the population, suggesting that large communities can foster the emergence of more complex opinions.

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Cite This Study

Ducasse et al. (2025) studied this question.

synapsesocial.com/papers/6984346ff1d9ada3c1fb2944https://doi.org/10.1051/mmnp/2025025/pdf
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