This repository contains the dataset used for analyzing the voting pattern with the timeline in mind. It was an effort to understand the voting across Day 1 - 7 on 143 Snapshot proposals the Arbitrum DAO members voted upon. Large Dataset file link is provided in the resources below as the size is too large to be uploaded here.
The "Analysis of Delegates Voting Patterns in Arbitrum Proposals" project aims to investigate the voting behaviors of delegates within the Arbitrum governance framework. Through rigorous statistical analysis of a comprehensive dataset, we seek to uncover consistent patterns and correlations in delegate voting across various proposals. The approach prioritizes systematic methodology and thorough documentation, aiming to provide valuable insights into delegate participation and decision-making dynamics.
The sub-task "Optimizing Voting Periods: An Analysis of Day-Wise Voting Patterns in Arbitrum Proposals" investigates the feasibility of shortening voting periods from 7 to 6 days. By analyzing day-to-day vote counts and voting power, we aim to identify opportunities for optimization while ensuring effective decision-making. This involves examining trends in vote distribution, identifying influential voters, and assessing the impact of last-day voting. The goal is to provide insights to streamline governance processes within the Arbitrum DAO ecosystem.
This project utilizes a variety of tools and resources for data collection, manipulation, and visualization. Below are the links to the tools used:
- Snapshot API Docs: For retrieving snapshot votes data. Visit Snapshot API Docs
- Pandas: A Python library for data manipulation and analysis. Pandas Documentation
- Plotly: A Python library for creating interactive visualizations. Plotly Python
- Lighthouse: For hosting visualization files. Lighthouse Documentation
- IPFS Pinata: For hosting the dataset. Dataset