{
  "abstract": "Background: Emotional contagion plays a crucial role in shaping group dynamics, interpersonal relationships, and affective regulation. Mathematical models of affect and agent-based models of emotional contagion are well established, but fewer formulations combine a continuous valence–arousal representation, explicit multi-agent coupling, time-continuous interaction dynamics, and mechanically interpretable dynamical parameters within a single framework. Objective: This study develops a mathematical and computational model of emotional contagion that integrates intra-individual affective dynamics and inter-individual affective influence within a time-dependent framework based on Russell’s Circumplex Model of Affect. Methods: Emotions are modeled as phasors in the complex plane, where each state evolves through the interaction of two oscillators: a radial oscillator for emotional intensity and an angular oscillator for affective direction. Emotional influence among agents is implemented through coupling matrices that allow dynamic simulation of contagion. The full system is expressed as a system of coupled first-order differential equations and solved numerically using Runge–Kutta integration schemes. Results: The simulations generated qualitative patterns of phase alignment, persistent state dispersion, leader-induced tracking, oscillatory amplification, and collective convergence under selected parameter and network configurations. They illustrate how attractors, damping, coupling strength, and network topology influence trajectories within the proposed mathematical framework. Conclusion: The proposed model offers a theoretically grounded and computationally tractable approach for studying emotional contagion and it should be regarded as an exploratory and hypothesis-generating computational framework. It has not been empirically calibrated or validated as a predictive or neurobiological model of human affective dynamics. Future work should estimate its parameters from empirical affective time series and evaluate its performance using held-out or out-of-sample observations. Nevertheless, the framework opens promising avenues for applications in psychology, affective computing, psychotherapy analytics, and socially intelligent systems.",
  "abstract_shown": true,
  "affiliations": [
    "Biotechnology Institute, Universidad Nacional de Colombia, Bogotá, Colombia",
    "Research Group in Modelling and Numerical Methods in Engineering - GNUM, Universidad Nacional de Colombia, Bogotá, Colombia",
    "Department of Mechanical and Mechatronics Engineering, Universidad Nacional de Colombia, Bogotá, Colombia",
    "School of Chemical Engineering, University of Birmingham, Birmingham, United Kingdom"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Diego Alexander Garzón-Alvarado"
    },
    {
      "affs": [
        1
      ],
      "name": "Carlos Alberto Duque-Daza"
    },
    {
      "affs": [
        2
      ],
      "name": "Alessio Alexiadis"
    },
    {
      "affs": [
        3
      ],
      "name": "Ricardo Mauricio Tamayo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bhs2qn721j58r.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0334738",
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  "id": "bhs2qn721j58r",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0334738",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3109|Opinion Dynamics and Social Influence"
    ],
    [
      "plos",
      "/Biology and life sciences/Evolutionary biology/Evolutionary processes/Convergent evolution"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Emotions"
    ],
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      "plos",
      "/Biology and life sciences/Psychology/Social psychology"
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      "plos",
      "/Computer and information sciences/Network analysis/Network reciprocity"
    ],
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      "plos",
      "/Computer and information sciences/Network analysis/Social networks"
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      "/Computer and information sciences/Systems science/Agent-based modeling"
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      "/Computer and information sciences/Systems science/Dynamical systems"
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      "/Physical sciences/Mathematics/Systems science/Dynamical systems"
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      "/Research and analysis methods/Simulation and modeling"
    ],
    [
      "plos",
      "/Research and analysis methods/Simulation and modeling/Agent-based modeling"
    ],
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      "plos",
      "/Social sciences/Psychology/Emotions"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Social psychology"
    ],
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      "plos",
      "/Social sciences/Sociology/Social networks"
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  "openalex": "W7213351471",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0334738&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-15",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/bhs2qn721j58r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0334738",
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      "url": "https://doi.org/10.1371/journal.pone.0334738"
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  "subjects": [
    {
      "field": "biology",
      "origin": "plos:evolutionary biology",
      "subfield": "evolutionary-biology"
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    {
      "field": "mathematics",
      "origin": "plos:dynamical systems",
      "subfield": "dynamical-systems"
    }
  ],
  "title": "A dynamical systems model of emotional contagion: Oscillatory coupling in the circumplex of affect",
  "title_text": "A dynamical systems model of emotional contagion: Oscillatory coupling in the circumplex of affect",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/bhs2qn721j58r",
  "venue": "PLOS One",
  "versions": []
}