As a project work, I looked at the dynamics of transactions in the Bitcoin cryptocurrency system. Delay times between consecutive payments were analysed to investigate their distribution - a distribution that could predict the next time an individual intends to spend money. This study is inspired by (Barabási 2005), a paper showing that human dynamics follow a fat-tailed power-law distribution in terms of certain tasks, like e-mail communication. It is yet to be examined if payment habits exhibit the same behavior or not. [Note: a fat-, or heavy-tailed distribution in this case is characterized by long waiting times, and burst like activities - e.g. we usually send e-mails in batches, time to time, and not in every hour a mail.]
Transactions, or payments, of 59490 accounts were fetched from the Bitcoin blockchain by calling the API of blockchain.info. Accounts were then filtered by the amount of payments initiated – minimum number of 60 transactions was required – in order to leave out bitcoin addresses used once (“Protect Your Privacy - Bitcoin” 2016) or just a few times. Account information of 6729 Bitcoin addresses made to the analysis phase in the end.
Inter-payment delay times of two accounts. Tall spikes suggests a heavy-tailed distribution - long waiting times (delay time in seconds).
