Abstract
Throughout the years, political scientists have devised a multitude of techniques to position political parties on various ideological and policy/issue dimensions. So far, however, none of these techniques was able to evolve into a “gold standard” in party positioning. Against this background, one could recently witness the appearance of a new methodology for party positioning tightly connected to the spread of Voting Advice Applications (VAAs), i.e. an iterative method that aims at improving existing techniques using a combination of party self-placement and expert judgement. Such a method, as pioneered by the Dutch Kieskompas, was first systematically employed on a large cross-national scale by the EU Profiler VAA in the context of the 2009 European Parliamentary elections. This article introduces the party placement datasets generated by
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