{
  "annotation_id": "78dcbf44-0ec6-4905-a4c3-966d26544803",
  "date_created": "2026-03-02T18:01:07.361000Z",
  "date_modified": "2026-03-02T18:01:07.361000Z",
  "file_hash": "587dfa6a944bd619b20d493c6ef926f6425c2ecdec6a20edfc5d37f81c68a889",
  "private": false,
  "record": {
    "abstract": "We study a general set of models of social network evolution and dynamics.\nThe models consist of both a dynamics on the network and evolution of the\nnetwork. Links are formed preferentially between \u0027similar\u0027 nodes, where the\nsimilarity is defined by the particular process taking place on the network.\nThe interplay between the two processes produces phase transitions and\nhysteresis, as seen using numerical simulations for three specific processes.\nWe obtain analytic results using mean field approximations, and for a\nparticular case we derive an exact solution for the network. In common with\nreal-world social networks, we find coexistence of high and low connectivity\nphases and history dependence.",
    "arxiv_id": "physics/0604036",
    "authors": [
      "George C. M. A. Ehrhardt",
      "Matteo Marsili",
      "Fernando Vega-Redondo"
    ],
    "categories": [
      "physics.soc-ph",
      "cond-mat.stat-mech"
    ],
    "doi": "10.1103/PhysRevE.74.036106",
    "title": "Phenomenological Models of Socio-Economic Network Dynamics",
    "url": "https://arxiv.org/abs/physics/0604036"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "90e42563-6743-48d7-a936-e41e51fbd192",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}