Spatial models in voting advice applications

Highlights

• The underlying spatial models of VAAs should be based on scientific standards.

• The GAL–TAN dimensions used in ten VAAs do not meet basic scalability requirements.

• The Left–Right dimensions used in ten VAAs do meet basic scalability requirements.

Abstract

We examine the use of spatial models in Voting Advice Applications. A successful branch of VAAs uses multidimensional models of the political space to inform users of their policy match with political parties. Creators of these VAAs offer only a very generalized justification for the choice of their underlying spatial model. We examine whether these spatial representations offer a valid depiction of policy differences between parties. We compare the spatial models from the available national ‘electoral compasses’, which include established democracies as well as semi-authoritarian and transitional systems. We find that the two-dimensional ‘one-size fits all’ model that is used in all of these countries fails to accommodate significant variation between party systems.

Introduction

Studies have shown that Voting Advice Applications (VAAs) play a substantial role in shaping voters' perceptions of the positions of political parties (see other articles in this symposium). Voters and politicians take the information these tools provide seriously. This places a strong obligation of VAA creators to carefully examine their design choices. Research has shown that differences in statement selection and the method to calculate results have a large impact on the advice users receive (Louwerse and Rosema, 2013, Lefevere and Walgrave, 2014). This makes it pivotal to study the reliability of VAA design. This article examines the spatial models underlying VAAs.

Some VAAs provide advice by asking respondents' opinions on a number of statements and calculating the number of matches between a user and a number of parties. More recently, VAAs have started to use spatial modelling techniques derived from economic and political science in an attempt to use “scientifically approved methods” to place political parties (cited in Fossen and Anderson, 2014). Examples of these VAAs include the series of ‘electoral compasses’ (such as Kieskompas, Bússola Eleitoral and Valkompass), the EU Profiler and Smartvote. These VAAs do not just inform citizens about their policy match with each party, but also provide insight into the positions of political parties in (a representation of) the political space. These tools provide citizens the option of exploring their agreement with parties more precisely but primarily presents the ‘match’ as closest party in the spatial models.¹ The creators of these VAAs usually provide only a very generalized justification for the choice of their underlying spatial model. In most cases, designers do not base their selection of which dimensions to include in their spatial model (such as left–right and progressive–conservative) on empirical patterns in the data (Costa Lobo et al., 2010).

This article aims to test whether the spatial models used in VAAs meet basic scientific standards. We specifically examine whether the spatial representations offer a valid depiction of policy differences between parties. We examine the spatial models of ten national VAAs, both in developed democracies such as Canada, as well as transitional democracies such as Tunisia.

The article is organized as follows. First, we discuss the use of spatial models in VAAs and the theoretical grounds for their usage. Second, we introduce our case selection of ten VAAs from the ‘electoral compass’ stable and outline their design. We examine the scalability of the various electoral compass dimensions and explore the inductive creation of models that fit parties' positions better. Results show that the scalability of the left–right scale is moderate to strong in most countries, but the scalability of the progressive–conservative scale is poor. Moreover, there is only a moderate fit between the model used in the electoral compasses and inductive models derived from parties' actual answers to the statements. This has significant implications for the status of the advice these applications provide, as the models in which voters and parties are placed are poorly specified and therefore it is unclear whether they are substantively meaningful.