{
  "annotation_id": "ed2020df-3382-4102-8f43-7aa680abcc32",
  "date_created": "2026-03-02T18:01:14.409000Z",
  "date_modified": "2026-03-02T18:01:14.409000Z",
  "file_hash": "2def8a12e8c2c7a275bf6dd1aba8301639bf2490f98d95606e864e8c11eb681f",
  "private": false,
  "record": {
    "abstract": "The collaboration network is an example of a social network which has both\nnon-trivial temporal and spatial dependence. Based on the observations of\ncollaborations in Physical Review Letters, a model of collaboration network is\nproposed which correctly reproduces the time evolution of the link length\ndistributions, clustering coefficients, degree distributions and assortative\nproperty of real data to a large extent.",
    "arxiv_id": "physics/0612069",
    "authors": [
      "Anjan Kumar Chandra",
      "Kamalika Basu Hajra",
      "Pratap Kumar Das",
      "Parongama Sen"
    ],
    "categories": [
      "physics.soc-ph",
      "physics.data-an"
    ],
    "doi": "10.1142/S0129183107011194",
    "title": "Modelling temporal and spatial features of collaboration network",
    "url": "https://arxiv.org/abs/physics/0612069"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "2d8e85c6-cbcb-42d0-b596-9e174c9ea85d",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}