Abstract
AbstractCryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies. In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.e. addresses do not tend for transact with a particular type of addresses of higher or lower degree, and the degree sequence of their transaction graph follows the power law distribution.
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computer Networks and Communications,Multidisciplinary
Reference26 articles.
1. ApacheSpark (2019) Unified Analytics Engine for Big Data. https://spark.apache.org. Accessed 20 Jan 2019.
2. Barabási, A-L (2009) Scale-free networks: A decade and beyond. Science 325(5939):412–413.
3. Barabási, A-L, Pósfai M (2016) Network Science. Cambridge University Press, Cambridge. http://barabasi.com/networksciencebook/.
4. Barabási, A-L, Ravasz E, Vicsek T (2001) Deterministic scale-free networks. Phys A: Stat Mech Appl 299(3):559–564.
5. Buterin, V (2014) A next-generation smart contract and decentralized application platform. white paper.
Cited by
42 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献