Empirical Analysis of DAO Governance Participation

Level: MA/MAP
Responsible person: Guangyao Li
Keywords:  DAO, Blockchain, Tokenomics, Token Engineering

Decentralized Autonomous Organizations (DAOs) are a novel form of organizational governance enabled by blockchain technology. Unlike traditional organizations, DAOs operate through smart contracts and community-driven proposals, with decision-making executed via token-based voting.  

Despite their growing importance, DAOs still face problems such as low voter participation, voter concentration among “whales,” coordination inefficiencies, and a lack of transparency in decision-making influence. However, systematic analyses of how DAOs make decisions, what factors influence proposal outcomes, and how governance participation evolves remain limited. Understanding these behavioral patterns is crucial for solving the mentioned problems and improving governance efficiency, voter engagement, and decentralization.  

This project/thesis aims to empirically analyze DAO decision-making patterns using publicly available data from big DAO platforms, e.g., Aragon and Snapshot. The main objectives are: 

1. Data collection: Collect, clean, and structure governance data (on-chain and off-chain, including proposals, votes, outcomes, etc.) from the DAO platforms. 

2. Behavioral Analysis: Identify patterns in participation rates, voting power concentration, and proposal success rates, etc.  

3. Security Analysis: Identify potential vulnerabilities such as coalitions, decision flips, and hidden majorities etc. 

4. Design improvement methods: Based on the findings, design better solutions and mechanisms for improvement, and if possible, prototype the design.