Matching voters with political parties and candidates: an empirical test of four algorithms

摘要

Voting Advice Applications (VAAs) have enjoyed a growing popularity across Europe in recent years and, increasingly, in other parts of the globe too. In response a growing literature is emerging around the promises and potential perils associated with VAAs. This paper contributes to these debates by addressing a core methodological aspect of VAA design: how voters' policy preferences are aggregated to produce measures of concordance with parties/candidates. To this end, the paper analyses the performance of four VAA models that are based on competing algorithms. The findings, which draw from the analysis of VAA-generated data from four experiments, raise a number of concerns for the future design of VAA systems.