VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making

• URL: http://arxiv.org/abs/2307.10903v2
• Date: Wed, 7 Aug 2024 15:21:29 GMT
• Title: VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making
• Authors: Renato Kunz, Fatemeh Banaie, Abhinav Sharma, Carina I. Hausladen, Dirk Helbing, Evangelos Pournaras,
• Abstract summary: This paper introduces VoteLab, an open-source 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. Voters can easily respond to subscribed voting questions on a smartphone.
• Score: 0.9503786527351696
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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