{
  "annotation_id": "95e0eabe-e9a1-4631-a27d-3a515640f049",
  "date_created": "2026-03-02T18:01:00.795000Z",
  "date_modified": "2026-03-02T18:01:00.795000Z",
  "file_hash": "b1ad8c3dab1cf1f6645085834106485b035ba0cc98a8ee0114277a1f688c01bd",
  "private": false,
  "record": {
    "abstract": "We present an analysis of a person-to-person recommendation network,\nconsisting of 4 million people who made 16 million recommendations on half a\nmillion products. We observe the propagation of recommendations and the cascade\nsizes, which we explain by a simple stochastic model. We analyze how user\nbehavior varies within user communities defined by a recommendation network.\nProduct purchases follow a \u0027long tail\u0027 where a significant share of purchases\nbelongs to rarely sold items. We establish how the recommendation network grows\nover time and how effective it is from the viewpoint of the sender and receiver\nof the recommendations. While on average recommendations are not very effective\nat inducing purchases and do not spread very far, we present a model that\nsuccessfully identifies communities, product and pricing categories for which\nviral marketing seems to be very effective.",
    "arxiv_id": "physics/0509039",
    "authors": [
      "Jure Leskovec",
      "Lada A. Adamic",
      "Bernardo A. Huberman"
    ],
    "categories": [
      "physics.soc-ph",
      "cond-mat.stat-mech",
      "cs.DB",
      "cs.DS"
    ],
    "doi": "10.1145/1232722.1232727",
    "journal_ref": "Leskovec, J., Adamic, L. A., and Huberman, B. A. 2007. The\n  dynamics of viral marketing. ACM Transactions on the Web, 1, 1 (May 2007)",
    "title": "The Dynamics of Viral Marketing",
    "url": "https://arxiv.org/abs/physics/0509039"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "57fe530f-995c-47e1-9f86-7ff7943f89af",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}