Egalitarian Society or Benevolent Dictatorship: The State of Cryptocurrency Governance

Abstract

In this paper we initiate a quantitative study of the decentralization of the governance structures of Bitcoin and Ethereum. In particular, we scraped the open-source repositories associated with their respective codebases and improvement proposals to find the number of people contributing to the code itself and to the overall discussion. We then present different metrics to quantify decentralization, both in each of the cryptocurrencies and, for comparison, in two popular open-source programming languages: Clojure and Rust. We find that for both cryptocurrencies and programming languages, there is usually a handful of people that accounts for most of the discussion. We also look into the effect of forks in Bitcoin and Ethereum, and find that there is little intersection between the communities of the original currencies and those of the forks.

Theory and Reality of Cryptocurrency Governance

“…Core programmers of the source code may benefit from volunteers by making the software available freely to everyone. Regarding the Bitcoin there is a concentration of programmers who contribute to the codebase and a concentration of commenters who propose changes to the codebase (Azouvi, Maller, and Meiklejohn 2018). It may result in different versions of the coin involved.…”

Short Paper: An Exploration of Code Diversity in the Cryptocurrency Landscape

“…In terms of comparing Bitcoin and Ethereum, Gencer et al [9] compared the level of decentralization in their peer-to-peer networks and found, for example, that Ethereum mining was more centralized than it was in Bitcoin, but that Bitcoin nodes formed more geographic clusters. Azouvi et al [2] also compared their level of decentralization, in terms of the discussions on and contributions to their GitHub repositories, and found that Ethereum was more centralized in terms of code contribution and both were fairly centralized in terms of the discussions. Gervais et al [10] introduced a framework for identifying the tradeoff between security and performance in any cryptocurrency based on proof-of-work, and found that the same level of resilience to double-spending attacks was achieved by 37 blocks in Ethereum as by 6 blocks in Bitcoin.…”

Blockchain Use Cases and Their Feasibility

“…One of the main concerns regarding decentralised networks is always about their control (see also [29]). For example, blockchains with a proof-of-work consensus algorithm are theoretically vulnerable to the so-called 51-percent attack, when one network node would have 51 % of total network computational power, thus gaining possibility to singlehandedly confirm transactions and create new blocks [2].…”