{
  "annotation_id": "27d8016b-22ee-44de-95b8-1d7b2e046364",
  "date_created": "2026-03-02T18:01:11.453000Z",
  "date_modified": "2026-03-02T18:01:11.453000Z",
  "file_hash": "567c6dc2290c9ca7d416956a8af61676acfe4c5802fac4ac75c355190d23c171",
  "private": false,
  "record": {
    "abstract": "Deviations from the average can provide valuable insights about the\norganization of natural systems. This article extends this important principle\nto the more systematic identification and analysis of singular local\nconnectivity patterns in complex networks. Four measurements quantifying\ndifferent and complementary features of the connectivity around each node are\ncalculated and multivariate statistical methods are then applied in order to\nidentify outliers. The potential of the presented concepts and methodology is\nillustrated with respect to a word association network.",
    "arxiv_id": "physics/0607272",
    "authors": [
      "Luciano da F. Costa",
      "Marcus Kaiser",
      "Claus Hilgetag"
    ],
    "categories": [
      "physics.data-an",
      "cond-mat.dis-nn",
      "physics.soc-ph"
    ],
    "title": "Beyond the average: detecting global singular nodes from local features   in complex networks",
    "url": "https://arxiv.org/abs/physics/0607272"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "46de2869-ce29-41a6-974e-a5c13aa01331",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}