While the design of voting advice applications (VAAs) is witnessing an increasing amount of attention, one aspect has until now been overlooked: its visualisations. This is remarkable, as it are those visualisations that communicate to the user the advice of the VAA. Therefore, this article aims to provide a first look at which visualisations VAAs adopt, why they adopt them, and how users comprehend them. For this, I will look at how design choices, specifically those on matching, influence the type of visualisation VAAs not only do but also have to, use. Second, I will report the results of a small-scale experiment that looked if all users comprehend similar visualisations in the same way. Here, I find that this is often not the case and that the interpretations of the users often differ. These first results suggest that VAA visualisations are wrongly underappreciated and demand closer attention of VAA designers.
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Statistics, Politics, and Policy studies the ways that statistical analysis drives public policy decisions, and publishes significant research on the application of statistical ideas to problems that relate to policy implementation.