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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.01015 |
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| _version_ | 1866910369984806912 |
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| author | Wang, Qian Zhang, Zhen Liu, Zemin Lu, Shengliang Luo, Bingqiao He, Bingsheng |
| author_facet | Wang, Qian Zhang, Zhen Liu, Zemin Lu, Shengliang Luo, Bingqiao He, Bingsheng |
| contents | While numerous public blockchain datasets are available, their utility is constrained by an exclusive focus on blockchain data. This constraint limits the incorporation of relevant social network data into blockchain analysis, thereby diminishing the breadth and depth of insight that can be derived. To address the above limitation, we introduce EX-Graph, a novel dataset that authentically links Ethereum and X, marking the first and largest dataset of its kind. EX-Graph combines Ethereum transaction records (2 million nodes and 30 million edges) and X following data (1 million nodes and 3 million edges), bonding 30,667 Ethereum addresses with verified X accounts sourced from OpenSea. Detailed statistical analysis on EX-Graph highlights the structural differences between X-matched and non-X-matched Ethereum addresses. Extensive experiments, including Ethereum link prediction, wash-trading Ethereum addresses detection, and X-Ethereum matching link prediction, emphasize the significant role of X data in enhancing Ethereum analysis. EX-Graph is available at \url{https://exgraph.deno.dev/}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_01015 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | EX-Graph: A Pioneering Dataset Bridging Ethereum and X Wang, Qian Zhang, Zhen Liu, Zemin Lu, Shengliang Luo, Bingqiao He, Bingsheng Social and Information Networks Artificial Intelligence While numerous public blockchain datasets are available, their utility is constrained by an exclusive focus on blockchain data. This constraint limits the incorporation of relevant social network data into blockchain analysis, thereby diminishing the breadth and depth of insight that can be derived. To address the above limitation, we introduce EX-Graph, a novel dataset that authentically links Ethereum and X, marking the first and largest dataset of its kind. EX-Graph combines Ethereum transaction records (2 million nodes and 30 million edges) and X following data (1 million nodes and 3 million edges), bonding 30,667 Ethereum addresses with verified X accounts sourced from OpenSea. Detailed statistical analysis on EX-Graph highlights the structural differences between X-matched and non-X-matched Ethereum addresses. Extensive experiments, including Ethereum link prediction, wash-trading Ethereum addresses detection, and X-Ethereum matching link prediction, emphasize the significant role of X data in enhancing Ethereum analysis. EX-Graph is available at \url{https://exgraph.deno.dev/}. |
| title | EX-Graph: A Pioneering Dataset Bridging Ethereum and X |
| topic | Social and Information Networks Artificial Intelligence |
| url | https://arxiv.org/abs/2310.01015 |