Bitcoin Research with a Transaction Graph Dataset
Not on the map. Why?
Abstract (arXiv)
Bitcoin, launched in 2008 by Satoshi Nakamoto, established a new digital economy where value can be stored and transferred in a fully decentralized manner - alleviating the need for a central authority. This paper introduces a large scale dataset in the form of a transactions graph representing transactions between Bitcoin users along with a set of tasks and baselines. The graph includes 252 million nodes and 785 million edges, covering a time span of nearly 13 years of and 670 million transactions. Each node and edge is timestamped. As for supervised tasks we provide two labeled sets i. a 33,000 nodes based on entity type and ii. nearly 100,000 Bitcoin addresses labeled with an entity name and an entity type. This is the largest publicly available data set of bitcoin transactions designed to facilitate advanced research and exploration in this domain, overcoming the limitations of existing datasets. Various graph neural network models are trained to predict node labels, establishing a baseline for future research. In addition, several use cases are presented to demonstrate the dataset's applicability beyond Bitcoin analysis. Finally, all data and source code is made publicly available to enable reproducibility of the results.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 19 of its 40 references that are in the map. First posted on arXiv 15 Nov 2024.
Builds on
19 of 40 references.
References · 19
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
- 2017Graph Attention Networkscited by 8,923
- 2017Inductive Representation Learning on Large Graphscited by 6,320
- 2018How Powerful are Graph Neural Networks?cited by 4,393
- 2018Graph Convolutional Neural Networks for Web-Scale Recommender Systemscited by 1,138
- 2023Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4cited by 202
- 2019Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensicscited by 164
- 2020DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphscited by 139
- 2018Ransomware Payments in the Bitcoin Ecosystemcited by 11
- 2024The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Datasetcited by 8
- 2018On the Economic Significance of Ransomware Campaigns: A Bitcoin Transactions Perspectivecited by 7
7 more
- 2022BABD: A Bitcoin Address Behavior Dataset for Pattern Analysiscited by 5
- 2019Spams meet Cryptocurrencies: Sextortion in the Bitcoin Ecosystemcited by 4
- 2022Watch Your Back: Identifying Cybercrime Financial Relationships in Bitcoin through Back-and-Forth Explorationcited by 4
- 2015Bitcoin-NG: A Scalable Blockchain Protocolcited by 3
- 2023Heuristics for Detecting CoinJoin Transactions on the Bitcoin Blockchaincited by 3
- 2022Pattern Analysis of Money Flow in the Bitcoin Blockchaincited by 2
- 2024Assessing the Efficacy of Heuristic-Based Address Clustering for Bitcoincited by 2
Built on by
Citing papers per year: 2026: 3.
3 papers.