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URL: https://dx.doi.org/DOI:10.17504/protocols.io.rc3d2yn

Authors: Jiaqi Liang

Summary: In this paper, we apply statistics and network analysis methods to explore the dynamic characteristics of three transaction networks. We download transaction data from the respective blockchain explorers. To the best of our knowledge, these are the largest datasets adopted in cryptocurrency analysis to date. We analyze the growth pattern of the accumulated network and find that unlike most networks, these cryptocurrency networks do not always densify over time. Then based on the datasets, we find that the monthly repetition ratios measured by either node or edge are relatively low. As such, studying the whole accumulated network, as done in most previous work, is not the appropriate way to understand the network dynamics. Hence we focus on coining the dynamics through computing the values of typical network measures on a monthly basis, and make a comparison among the three networks. 

Affiliations: State Key Laboratory of Management and Control for Complex Systems, Institute of Automation,Chinese Academy of Sciences, China; School of Computer and Control Engineering, University of Chinese Academy of Sciences, China

Version: 1

Publication Date: 2018

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