{
  "annotation_id": "9cf1641d-b96c-4c8d-93d8-833ab33ce2ab",
  "date_created": "2026-03-02T18:01:04.284000Z",
  "date_modified": "2026-03-02T18:01:04.284000Z",
  "file_hash": "b9cbe5620c538b77a5470db209747a09268b8a03b56ed8391e0f6814b48e9c23",
  "private": false,
  "record": {
    "abstract": "We study the topology of several music recommendation networks, which rise\nfrom relationships between artist, co-occurrence of songs in playlists or\nexperts\u0027 recommendation. The analysis uncovers the emergence of complex network\nphenomena in this kind of recommendation networks, built considering artists as\nnodes and their resemblance as links. We observe structural properties that\nprovide some hints on navigation and possible optimizations on the design of\nmusic recommendation systems. Finally, the analysis derived from existing music\nknowledge sources provides a deeper understanding of the human music similarity\nperceptions.",
    "arxiv_id": "physics/0512266",
    "authors": [
      "Pedro Cano",
      "Oscar Celma",
      "Markus Koppenberger",
      "Javier M. Buld\u00fa"
    ],
    "categories": [
      "physics.soc-ph"
    ],
    "doi": "10.1063/1.2137622",
    "journal_ref": "Chaos, 16, 013107 (2006)",
    "title": "The Topology of Music Recommendation Networks",
    "url": "https://arxiv.org/abs/physics/0512266"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "94767e33-a836-447c-a3a5-d7f4f208702b",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}