{
  "abstract": "Social Physics seeks quantitative, empirically testable explanations of collective human behavior. Its name has a long and contested history, but its contemporary program is neither the claim that society is literally a physical system nor an attempt to replace the social sciences with physics. It is an interdisciplinary practice: observation and experimentation, model construction, mathematical and computational analysis, and repeated confrontation with data. The field has been transformed by analyzing digital traces, network science, agent-based modeling, large-scale experiments, and the capacity to study coupled dynamics across economic, social, technological, biological, and physical layers. We review advances in financial analysis and modeling; economic complexity; the structure and evolution of social networks; spreading, opinion, and information dynamics; inequality, cooperation, conflict, mobility, cities, culture, science, and collective behavior; and the emerging study of human-AI ecosystems. Across these domains, common features recur - heterogeneity, interaction, feedback, adaptation, non-equilibrium dynamics, multiscale organization, and emergent collective outcomes. We also confront the limitations that have arisen in this field: convenience samples, platform dependence, weak causal identification, over-universal claims, insufficient engagement with meaning and institutions, privacy risks, and the danger that predictive models become instruments of manipulation. We propose a future Social Physics organized around theory - data reciprocity; causal and generative explanation; measurement validity and cross-context generalization; responsible, participatory data governance; genuinely interdisciplinary collaboration; and reflexive study of interventions and algorithms that alter the systems being observed.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.08117",
  "author_total": 22,
  "authors": [
    {
      "name": "János Kertész"
    },
    {
      "name": "Marc Barthelemy"
    },
    {
      "name": "Guido Caldarelli"
    },
    {
      "name": "Bikas K. Chakrabarti"
    },
    {
      "name": "Tiziana Di Matteo"
    },
    {
      "name": "Serge Galam"
    },
    {
      "name": "Marta Gonzales"
    },
    {
      "name": "Yurij Holovatch"
    },
    {
      "name": "Janusz A. Holyst"
    },
    {
      "name": "Sarika Jalan"
    },
    {
      "name": "Hawoong Jeong"
    },
    {
      "name": "Neil F. Johnson"
    },
    {
      "name": "Renaud Lambiotte"
    },
    {
      "name": "Linyuan Lü"
    },
    {
      "name": "Thomas Lux"
    },
    {
      "name": "Rosario N. Mantegna"
    },
    {
      "name": "Matjaz Perc"
    },
    {
      "name": "Jari Saramäki"
    },
    {
      "name": "Michael Small"
    },
    {
      "name": "Misako Takayasu"
    },
    {
      "name": "Taha Yasseri"
    },
    {
      "name": "Wei-Xing Zhou"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bw5yv380x1jsv.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.08117",
  "fulltext_url": null,
  "id": "bw5yv380x1jsv",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.08117",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.soc-ph"
    ],
    [
      "openalex",
      "2002|Complex Systems and Time Series Analysis"
    ]
  ],
  "openalex": "W7221054065",
  "pdf_url": "https://arxiv.org/pdf/2610.08117",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bw5yv380x1jsv.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:54Z",
      "native_id": "2610.08117",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.08117"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.soc-ph",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Social Physics: A manifesto",
  "title_text": "Social Physics: A manifesto",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:54Z",
  "url": "https://research.draconitic.com/paper/bw5yv380x1jsv",
  "venue": "arXiv",
  "versions": []
}