Data Depth and Core-based Trend Detection on Blockchain Transaction Networks

arXiv:2303.14241v2 Announce Type: replace-cross
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 …

arxiv assets blockchain blockchains complexity cs.cr cs.lg daily data depth detection dollars finance market networks trade transaction trend