Analyzing Voting Power in Decentralized Governance: Who controls DAOs?

• URL: http://arxiv.org/abs/2204.01176v1
• Date: Sun, 3 Apr 2022 22:58:01 GMT
• Title: Analyzing Voting Power in Decentralized Governance: Who controls DAOs?
• Authors: Robin Fritsch, Marino M\"uller and Roger Wattenhofer
• Abstract summary: We study the state of three prominent governance systems on the blockchain: Compound, Uniswap and ENS. Using a comprehensive dataset of all governance token holders, delegates, proposals and votes, we analyze who holds the voting rights and how they are used to influence governance decisions.
• Score: 21.764659973662173
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We empirically study the state of three prominent DAO governance systems on the Ethereum blockchain: Compound, Uniswap and ENS. In particular, we examine how the voting power is distributed in these systems. Using a comprehensive dataset of all governance token holders, delegates, proposals and votes, we analyze who holds the voting rights and how they are used to influence governance decisions.

Related papers

• Kite: How to Delegate Voting Power Privately [11.967243519550625]
  We introduce Kite, a protocol that enables $textitprivate$ delegation of voting power for members. Voters can freely delegate, proofs, and re-delegate their power without revealing any information about who they delegated to. The only information that is recorded publicly is that the voter delegated or re-delegated their vote to someone.
  arXiv  Detail & Related papers  (2025-01-09T23:49:45Z)
• Future of Algorithmic Organization: Large-Scale Analysis of Decentralized Autonomous Organizations (DAOs) [45.02792904507959]
  Decentralized Autonomous Organizations (DAOs) resemble early online communities, particularly those centered around open-source projects. In just a few years, the deployment of governance tokens surged with a total of $24.5 billion and 11.1M governance token holders collectively managing decisions across over 13,000s as of 2024. We examine factors such as voting power, participation, and characteristics dictating the level of decentralization, thus, the efficiency of management structures.
  arXiv  Detail & Related papers  (2024-10-16T23:45:10Z)
• From Experts to the Public: Governing Multimodal Language Models in Politically Sensitive Video Analysis [48.14390493099495]
  This paper examines the governance of large language models (MM-LLMs) through individual and collective deliberation. We conducted a two-step study: first, interviews with 10 journalists established a baseline understanding of expert video interpretation; second, 114 individuals from the general public engaged in deliberation using Inclusive.AI.
  arXiv  Detail & Related papers  (2024-09-15T03:17:38Z)
• Representation Bias in Political Sample Simulations with Large Language Models [54.48283690603358]
  This study seeks to identify and quantify biases in simulating political samples with Large Language Models. Using the GPT-3.5-Turbo model, we leverage data from the American National Election Studies, German Longitudinal Election Study, Zuobiao dataset, and China Family Panel Studies.
  arXiv  Detail & Related papers  (2024-07-16T05:52:26Z)
• Blockchain Governance: An Empirical Analysis of User Engagement on DAOs [0.0]
  We examine voting on four major blockchains: Aave, Compound, Lido and Uniswap. We find that in most votes, the "minimal quorum," i.e., the smallest number of active voters who could swing the vote is quite small.
  arXiv  Detail & Related papers  (2024-07-15T17:43:02Z)
• Combining AI Control Systems and Human Decision Support via Robustness and Criticality [53.10194953873209]
  We extend a methodology for adversarial explanations (AE) to state-of-the-art reinforcement learning frameworks. We show that the learned AI control system demonstrates robustness against adversarial tampering. In a training / learning framework, this technology can improve both the AI's decisions and explanations through human interaction.
  arXiv  Detail & Related papers  (2024-07-03T15:38:57Z)
• Liquid Democracy in DPoS Blockchains [4.42985313903391]
  Liquid democracy, also known as delegative voting, allows voters to vote directly or delegate their voting power to others. This paper explores the practical implementation of liquid democracy in Delegated-Proof-of-Stake (DPoS) blockchain systems.
  arXiv  Detail & Related papers  (2023-09-03T06:04:11Z)
• Unpacking How Decentralized Autonomous Organizations (DAOs) Work in Practice [54.47385318258732]
  Decentralized Autonomous Organizations (DAOs) have emerged as a novel way to coordinate a group of entities towards a shared vision. In just a few years, over 4,000 DAOs have been launched in various domains, such as investment, education, health, and research. Despite such rapid growth and diversity, it is unclear how theses actually work in practice and to what extent they are effective in achieving their goals.
  arXiv  Detail & Related papers  (2023-04-17T01:30:03Z)
• Private Multi-Winner Voting for Machine Learning [48.0093793427039]
  We propose three new DP multi-winner mechanisms: Binary, $tau$, and Powerset voting. Binary voting operates independently per label through composition. $tau$ voting bounds votes optimally in their $ell$ norm for tight data-independent guarantees. Powerset voting operates over the entire binary vector by viewing the possible outcomes as a power set.
  arXiv  Detail & Related papers  (2022-11-23T20:06:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.