Bitcoin, euro, ether, SPY

The purpose of the dataset is to compare the diffusion of bitcoin, the euro, ethereum, and the security SPY. If the diffusion was r-shaped, then it occurred through environmental learning-based (individual learning-based) adoption; if the diffusion was s-shaped, then it occurred through cultural transmission-based adoption (Henrich 2001). The large-scale diffusion of technology-based products generally occurs through cultural transmission and traces out s-shaped curves (Marinakis 2012, Marinakis et al. 2018). The number of euros in circulation shows how currency diffuses. The time series of the total number of Bitcoin that have already been mined was obtained from Blockchain. The time series of the diffusion of the number of euro bank notes and coins was obtained from the European Central Bank website. For further comparisons and insights, diffusion data of another cryptocurrency, ether, and of a security, SPY, were also obtained.

The data sets are comma delimited and comprise daily data.

The file total-bitcoins.csv has the format:
date, number of bitcoins minted

The file euro.csv has the format:
date, number of euros in circulation (bank notes and coins)

The file ether.csv has the format:
date, UnixTime, number of ether minted

The file SPY.csv has the format:
date, net asset value, shares outstanding, total net assets

本数据集旨在对比比特币（Bitcoin）、欧元（Euro）、以太坊（Ethereum）与证券SPY（SPY）的扩散规律。若资产扩散曲线呈R型，则其用户采用过程基于环境学习（或称个体学习）路径；若扩散曲线呈S型，则其采用过程依托文化传播机制（Henrich, 2001）。技术类产品的大规模扩散通常遵循文化传播路径，并呈现S型曲线特征（Marinakis, 2012；Marinakis等, 2018）。

欧元流通规模可用于表征货币的扩散过程。已开采比特币总供应量的时间序列数据取自Blockchain平台。欧元纸币与硬币总发行量的时间序列数据取自欧洲中央银行官方网站。为开展更全面的对比分析并获取更多研究洞见，本数据集还纳入了另一加密货币以太币（Ether）以及证券SPY（SPY）的扩散数据。

本数据集采用逗号分隔格式，所有数据均为日度频率。

各数据文件格式说明如下：
1. total-bitcoins.csv：日期, 已铸造比特币数量
2. euro.csv：日期, 流通中欧元总量（含纸币与硬币）
3. ether.csv：日期, Unix时间戳（UnixTime）, 已铸造以太币数量
4. SPY.csv：日期, 资产净值, 流通股数, 总净资产