VoteLab: A Modular and Adaptive Experimentation Platform for Online
Collective Decision Making
- URL: http://arxiv.org/abs/2307.10903v1
- Date: Thu, 20 Jul 2023 14:26:21 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: 2.8225382405626394
- 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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