Mayura introduces the MG-Tree, a hierarchical prefix tree over temporal motifs, enabling exact co-mining of multiple motifs with 1.7-2.4x average speedups on GPU/CPU.
The rich still get richer: Empirical comparison of preferential attachment via linking statistics in Bitcoin and Ethereum
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Bitcoin and Ethereum transactions present one of the largest real-world complex networks that are publicly available for study, including a detailed picture of their time evolution. As such, they have received a considerable amount of attention from the network science community, beside analysis from an economic or cryptography perspective. Among these studies, in an analysis on the early instance of the Bitcoin network, we have shown the clear presence of the preferential attachment, or "rich-get-richer" phenomenon. Now, we revisit this question, using a recent version of the Bitcoin network that has grown almost 100-fold since our original analysis. Furthermore, we additionally carry out a comparison with Ethereum, the second most important cryptocurrency. Our results show that preferential attachment continues to be a key factor in the evolution of both the Bitcoin and Ethereum transactoin networks. To facilitate further analysis, we publish a recent version of both transaction networks, and an efficient software implementation that is able to evaluate linking statistics necessary for learn about preferential attachment on networks with several hundred million edges.
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Mayura: Exploiting Similarities in Motifs for Temporal Co-Mining
Mayura introduces the MG-Tree, a hierarchical prefix tree over temporal motifs, enabling exact co-mining of multiple motifs with 1.7-2.4x average speedups on GPU/CPU.