{
  "abstract": "We study continuous-time relational event data, where time-stamped dyadic interactions reflect both individual node propensities and evolving relational proximity. We propose a dynamic latent space model for inhomogeneous Poisson processes, where event intensities depend on node-specific activity parameters and time-varying latent distances modeled via flexible B-splines. We prove model identifiability by decoupling baseline activity from latent position, ensuring high interaction volumes do not warp the spatial map. For scalability, we develop a minibatch stochastic gradient algorithm with stable initialization and geometric anchoring, alongside an effective-degrees-of-freedom BIC for tuning model complexity. Simulations confirm accurate parameter recovery and out-of-sample prediction. Applied to cooperative diplomatic events among 60 major economies (1995--2022), the model uncovers shifting patterns of international cooperation and isolates mobile geopolitical actors from stationary institutional anchors.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.08813",
  "author_total": 3,
  "authors": [
    {
      "name": "Jie Jian"
    },
    {
      "name": "Jiguo Cao"
    },
    {
      "name": "Owen G. Ward"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dbhrcrwvy9x6f.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.08813",
  "fulltext_url": null,
  "id": "dbhrcrwvy9x6f",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.08813",
  "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",
      "stat.AP"
    ],
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "arxiv",
      "stat.ML"
    ],
    [
      "openalex",
      "3109|Complex Network Analysis Techniques"
    ]
  ],
  "openalex": "W7212073852",
  "pdf_url": "https://arxiv.org/pdf/2609.08813",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dbhrcrwvy9x6f.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:17Z",
      "native_id": "2609.08813",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.08813"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Dynamic Latent Space Modeling of Inhomogeneous Poisson Network Processes with Applications to International Relations",
  "title_text": "Dynamic Latent Space Modeling of Inhomogeneous Poisson Network Processes with Applications to International Relations",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:17Z",
  "url": "https://research.draconitic.com/paper/dbhrcrwvy9x6f",
  "venue": "arXiv",
  "versions": []
}