VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making
Abstract
Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and elections. However, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and thoroughly-documented platform for modular and adaptive design of voting experiments. It supports to visually and interactively build reusable campaigns with a choice of different voting methods, while voters can easily respond to subscribed voting questions on a smartphone. A proof-of-concept with four voting methods and questions on COVID-19 in an online lab experiment have been used to study the consistency of voting outcomes. It demonstrates the capability of VoteLab to support rigorous experimentation of complex voting scenarios.
Keywords
Cite
@article{arxiv.2307.10903,
title = {VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making},
author = {Renato Kunz and Fatemeh Banaie and Abhinav Sharma and Carina I. Hausladen and Dirk Helbing and Evangelos Pournaras},
journal= {arXiv preprint arXiv:2307.10903},
year = {2024}
}