Rapidly growing distributed ledger technologies (DLTs) have recently received attention among researchers in both industry and academia. While a lot of existing analysis (mainly) of the Bitcoin and Ethereum networks is available, the lack of measurements for other crypto projects is observed. This article addresses questions about tokenomics and wealth distributions in cryptocurrencies. We analyze the time-dependent statistical properties of top cryptocurrency holders for 14 different distributed ledger projects. The provided metrics include approximated Zipf coefficient, Shannon entropy, Gini coefficient, and Nakamoto coefficient. We show that there are quantitative differences between the coins (cryptocurrencies operating on their own independent network) and tokens (which operate on top of a smart contract platform). Presented results show that coins and tokens have different values of approximated Zipf coefficient and centralization levels. This work is relevant for DLTs as it might be useful in modeling and improving the committee selection process, especially in decentralized autonomous organizations (DAOs) and delegated proof of stake (DPoS) blockchains.
翻译:最近,工业和学术界研究人员都注意到迅速分布的分类账技术(DLTs)最近得到迅速分布的研究人员的注意,虽然目前对Bitcoin和Etheum网络进行了许多分析(主要),但对其他加密项目缺乏测量,这篇文章涉及在加密过程中的象征性和财富分配问题,我们分析了14个分布的分类账项目最高加密货币持有者的时间依赖统计特性,所提供的衡量标准包括大约Zipf系数、香农通气、吉尼系数和中本系数。我们表明,硬币(在自己的独立网络上运行的硬币)和符号(在智能合同平台上运行的)之间在数量上存在差异,展示的结果显示,硬币和符号的近似Zipf系数和集中等级值不同。这项工作与DLTs有关,因为它可能有助于委员会的选择过程的建模和改进,特别是在分散的自治组织(DAOs)和委托的股份凭证(DPOS)链。