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Data Depth and Core-based Trend Detection on Blockchain Transaction Networks
May 7, 2024, 4:44 a.m. | Jason Zhu, Arijit Khan, Cuneyt Gurcan Akcora
cs.LG updates on arXiv.org arxiv.org
Abstract: Blockchains are significantly easing trade finance, with billions of dollars worth of assets being transacted daily. However, analyzing these networks remains challenging due to the sheer volume and complexity of the data. We introduce a method named InnerCore that detects market manipulators within blockchain-based networks and offers a sentiment indicator for these networks. This is achieved through data depth-based core decomposition and centered motif discovery, ensuring scalability. InnerCore is a computationally efficient, unsupervised approach suitable …
abstract arxiv blockchain blockchains complexity core cs.cr cs.lg daily data detection finance however market networks trade trend type
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