{
  "name": "bitcoin-otc",
  "sources": [
    {
      "url": "https://snap.stanford.edu/data/soc-sign-bitcoinotc.csv.gz",
      "final_url": "https://snap.stanford.edu/data/soc-sign-bitcoinotc.csv.gz",
      "filename": "soc-sign-bitcoinotc.csv.gz",
      "bytes": 397258,
      "sha256": "6424ac981dad3a019f697fc1b9fcd85c19d8d9f039797758e9ffb6fea100c373",
      "downloaded_at": "2026-07-23T02:14:57+00:00"
    }
  ],
  "title": "Bitcoin OTC Trust Network",
  "band": "small",
  "label_type": "anomaly",
  "task": "Fraudulent-user detection (derived labels)",
  "license": "SNAP research use; cite",
  "citation": "Kumar, Spezzano, Subrahmanian, Faloutsos. Edge Weight Prediction in Weighted Signed Networks. ICDM 2016. Labels: Kumar et al. REV2, WSDM 2018.",
  "links": [
    "https://snap.stanford.edu/data/soc-sign-bitcoin-otc.html"
  ],
  "conversion": {
    "script": "convert_bitcoin_otc.py",
    "label_column": "trust_label",
    "labeling_rule": {
      "method": "Recursive Web-of-Trust (REV2/Fraudar recipe, TAS-GNN operationalization)",
      "normalization": "rating / 10 -> [-1, +1]",
      "seeds": "top-5 PageRank nodes of the positive subgraph (founder proxies)",
      "benign": "recursive: any rating >= +0.5 (raw +5) from a Benign node",
      "fraudulent": "any rating <= -0.5 (raw -5) from a Benign node; negative ratings from non-benign raters ignored",
      "seed_ids": [
        1,
        7,
        35,
        1810,
        2642
      ],
      "benign_count": 636,
      "fraudulent_count": 614,
      "unknown_count": 4631
    },
    "notes": "Derived 3-class trust_label (benign/fraudulent/unknown) via the recursive Web-of-Trust recipe; evaluate classifiers on the labeled subset only, egonets use the full graph. Rated-pair structure symmetrized; rating signs/weights and timestamps not carried into edges. Label-only nodes.csv: rating aggregates would leak the derived label.",
    "parquet": true
  },
  "graphs": {
    "default": {
      "nodes": 5881,
      "edges": 21492,
      "label_column": "trust_label",
      "classes": 3,
      "class_counts": {
        "unknown": 4631,
        "benign": 636,
        "fraudulent": 614
      },
      "isolated_nodes": 0,
      "feature_columns": 0
    }
  }
}