{"url":"/dataset/gambling-contract-dataset","name":"Gambling Contract Dataset","full_name":null,"description_markdown":"**Gambling Contract Dataset** is a collection of 260 gambling smart contracts from decentralized gambling websites, such as Dicether, Degens. At the same time, in order to construct the negative samples required for training, 1040 smart contracts that are not involved in gambling (e.g., erc20, erc721, mixer, etc.) are selected . In the dataset, accounts are used to refer to contracts (e.g. 0x3fe2b...f8a33f), where 1, 0, and -1 to represent the gamble, non-gamble, and other types, respectively.\r\n\r\nSource: [Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods](https://arxiv.org/pdf/2211.14779v1.pdf)\r\n\r\nImage Source: [https://arxiv.org/pdf/2211.14779v1.pdf](https://arxiv.org/pdf/2211.14779v1.pdf)","description_withheld":null,"homepage":"https://github.com/awesomehuang/bitcoin-gambling-dataset","introduced_date":"2022-11-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/who-is-gambling-finding-cryptocurrency","title":"Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods","first_author":"Zhengjie Huang","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"}],"languages":[],"variants":["Gambling Contract Dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}