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Digital democracy and new forms for direct digital participation in policymaking gain unprecedented momentum. This is particularly the case forpreferential voting methods and decision-support systems designed to promotefairer, more inclusive and legitimate collective decision-making processes incitizens assemblies, participatory budgeting and elections. However, asystematic human experimentation with different voting methods is cumbersomeand costly. This paper introduces VoteLab, an open-source andthoroughly-documented platform for modular and adaptive design of votingexperiments. It supports to visually and interactively build reusable campaignswith a choice of different voting methods, while voters can easily respond tosubscribed voting questions on a smartphone. A proof-of-concept with fourvoting methods and questions on COVID-19 in an online lab experiment have beenused to study the consistency of voting outcomes. It demonstrates thecapability of VoteLab to support rigorous experimentation of complex votingscenarios.

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