{
  "annotation_id": "00d09899-9d27-4add-ab29-83c4218e5461",
  "date_created": "2026-03-02T18:01:18.026000Z",
  "date_modified": "2026-03-02T18:01:18.026000Z",
  "file_hash": "7b77e9d3eb563ea225fcb2f178648f7e9e6836d55766e12e8aa17be4d6f39510",
  "private": false,
  "record": {
    "abstract": "We examine the evolution of the vocabulary of a group of individuals\n(linguistic agents) on a scale-free network, using Monte Carlo simulations and\nassumptions from evolutionary game theory. It is known that when the agents are\narranged in a two-dimensional lattice structure and interact by diffusion and\nencounter, then their final vocabulary size is the maximum possible. Knowing\nall available words is essential in order to increase the probability to\n``survive\u0027\u0027 by effective reproduction. On scale-free networks we find a\ndifferent result. It is not necessary to learn the entire vocabulary available.\nSurvival chances are increased by using the vocabulary of the ``hubs\u0027\u0027 (nodes\nwith high degree). The existence of the ``hubs\u0027\u0027 in a scale-free network is the\nsource of an additional important fitness generating mechanism.",
    "arxiv_id": "physics/0701087",
    "authors": [
      "Alkiviadis Kalampokis",
      "Kosmas Kosmidis",
      "Panos Argyrakis"
    ],
    "categories": [
      "physics.soc-ph"
    ],
    "doi": "10.1016/j.physa.2006.12.048",
    "title": "Evolution of Vocabulary on Scale-free and Random Networks",
    "url": "https://arxiv.org/abs/physics/0701087"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "f7fd23a0-a151-45dd-8273-8740c9ac383d",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}