City Research Online

Quantifying and modelling online decentralised systems: a complex systems approach

ElBahrawy, A. Y. (2020). Quantifying and modelling online decentralised systems: a complex systems approach. (Unpublished Doctoral thesis, City, University of London)


Cryptocurrencies are unique examples of decentralised socioeconomic systems. All the transactions, trading, and development are traceable and publicly available. Bitcoin, the first cryptocurrency, was introduced in 2009 launching a market of more than 2500 cryptocurrencies and has a value of more than 200 billion dollars. In comparison to the rising importance of cryptocurrencies in the financial world, the research on cryptocurrencies is still limited. In this thesis, we analyse three novel datasets namely, cryptocurrencies’ market data, cryptocurrencies’ Wikipedia page views and edits, and illicit transactions on Bitcoin. We study the cryptocurrencies ecosystem, including the market dynamics, the social attention and the transaction network. We find that the ecological neutral model can capture the market dynamics, hinting at the extent to which technological differences between cryptocurrencies are considered in investment decisions. We also investigate the relationship between information production and consumption and cryptocurrency market dynamics. We find that a small community of tightly connected editors is responsible for most of the production of information about cryptocurrencies in Wikipedia. Finally, we assess dark markets’ Bitcoin transactions showing the ability of the markets to adapt to multiple closures, including law enforcement raids. We expect that our contribution will be of interest to researchers working on either cryptocurrencies or complex systems. We anticipate that adopting a complex systems approach, will spark more research that interweaves both the technological and socioeconomic aspect of cryptocurrencies.

Publication Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics
Departments: Doctoral Theses
School of Science & Technology > School of Science & Technology Doctoral Theses
School of Science & Technology > Mathematics
Text - Accepted Version
Download (19MB) | Preview



Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login