The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China.
PLoS One. 2018 Aug 17;13(8):e0202202. doi: 10.1371/journal.pone.0202202. eCollection 2018.
Cryptocurrency is a well-developed blockchain technology application that is currently a heated topic throughout the world. The public availability of transaction histories offers an opportunity to analyze and compare different cryptocurrencies. In this paper, we present a dynamic network analysis of three representative blockchain-based cryptocurrencies: Bitcoin, Ethereum, and Namecoin. By analyzing the accumulated network growth, we find that, unlike most other networks, these cryptocurrency networks do not always densify over time, and they are changing all the time with relatively low node and edge repetition ratios. Therefore, we then construct separate networks on a monthly basis, trace the changes of typical network characteristics (including degree distribution, degree assortativity, clustering coefficient, and the largest connected component) over time, and compare the three. We find that the degree distribution of these monthly transaction networks cannot be well fitted by the famous power-law distribution, at the same time, different currency still has different network properties, e.g., both Bitcoin and Ethereum networks are heavy-tailed with disassortative mixing, however, only the former can be treated as a small world. These network properties reflect the evolutionary characteristics and competitive power of these three cryptocurrencies and provide a foundation for future research.
加密货币是一种成熟的区块链技术应用，目前在全球范围内备受关注。交易历史的公开可用性为分析和比较不同的加密货币提供了机会。在本文中，我们对三种基于区块链的代表性加密货币（比特币、以太坊和 Namecoin）进行了动态网络分析。通过分析累积的网络增长，我们发现，与大多数其他网络不同，这些加密货币网络并不总是随着时间的推移而变得更加密集，而是随着时间的推移不断变化，节点和边的重复率相对较低。因此，我们随后按月构建单独的网络，跟踪典型网络特征（包括度分布、度聚类系数和最大连通分量）随时间的变化，并对这三种加密货币进行比较。我们发现，这些月度交易网络的度分布不能很好地拟合著名的幂律分布，同时，不同的货币仍然具有不同的网络特性，例如，比特币和以太坊网络都是长尾分布且具有负的节点聚类系数，但是，只有前者可以被视为小世界网络。这些网络特性反映了这三种加密货币的演化特征和竞争能力，为未来的研究提供了基础。
