加密货币交易网络的演化动力学 实证研究

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摘要翻译：
加密货币是一种成熟的区块链技术应用，是当前全球的热点话题。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。本文对三种具有代表性的基于区块链的加密货币：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而变密，它们一直在变化，节点和边缘重复率相对较低。因此，我们每月构建一个独立的网络，跟踪典型网络特征（包括度分布、度匹配性、聚类系数和最大连通分量）随时间的变化，并对三者进行比较。我们发现，这些月交易网络的度分布不能用著名的幂律分布很好地拟合，同时，不同的货币仍然具有不同的网络性质，如比特币和以太坊网络都是重尾的不协调混合，但只有前者可以被视为一个小世界。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，为今后的研究提供了基础。
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英文标题：
《Evolutionary dynamics of cryptocurrency transaction networks: An
  empirical study》
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作者：
Jiaqi Liang, Linjing Li, Daniel Zeng
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最新提交年份：
2018
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Computer Science        计算机科学
二级分类：Cryptography and Security        密码学与安全
分类描述：Covers all areas of cryptography and security including authentication, public key cryptosytems, proof-carrying code, etc. Roughly includes material in ACM Subject Classes D.4.6 and E.3.
涵盖密码学和安全的所有领域，包括认证、公钥密码系统、携带证明的代码等。大致包括ACM主题课程D.4.6和E.3中的材料。
--
一级分类：Computer Science        计算机科学
二级分类：Distributed, Parallel, and Cluster Computing        分布式、并行和集群计算
分类描述：Covers fault-tolerance, distributed algorithms, stabilility, parallel computation, and cluster computing. Roughly includes material in ACM Subject Classes C.1.2, C.1.4, C.2.4, D.1.3, D.4.5, D.4.7, E.1.
包括容错、分布式算法、稳定性、并行计算和集群计算。大致包括ACM学科类C.1.2、C.1.4、C.2.4、D.1.3、D.4.5、D.4.7、E.1中的材料。
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一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

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英文摘要：
  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.
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PDF链接：
https://arxiv.org/pdf/1808.08585

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关键词：货币交易 实证研究 动力学 交易网 distribution Ethereum 加密 具有 networks 特征