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Polling politics, media and election campagins. Literatuursignalering van een artikel uit Public Opinion Quarterly 69/5 en van een artikel uit Applied Linguistics 26/4

Voting Advice Applications are online tools that provide users with a voting advice based on their answers to a set of political attitude questions. This study investigated to what extent VAA users understand the questions that lead to the voting advice, and what search and response behaviour they expose in case of comprehension difficulties. Two studies were conducted to investigate these issues: a cognitive interviewing study among 60 VAA users during the Dutch municipal elections in the city of Utrecht, and a statistical analysis of all answers provided by 357,858 users who accessed one of the 34 municipal VAAs during these same elections. Results of the two studies show a coherent picture: difficult concepts (e.g., tax names or municipal jargon), geographical locations (e.g., reference to a specific street), and vague quantifying terms (e.g., "more") all complicate the question. In case of comprehension difficulties, Study 1 shows that VAA users make little effort to solve their problems, for example by looking up difficult terms on the Internet. Instead, they draw inferences about what the question might mean and proceed to answer nonetheless. These are often neutral or no opinion answers, which seems to suggest that the meanings of those options are confounded. In Study 2, however, we found that the choice for either a neutral or no opinion response is not accidental: semantic meaning problems often result in no opinion answers, whereas pragmatic problems are related to neutral responses. We discuss the implications of these findings for survey theory and practice.

Study 1 is a think-aloud study among 60 VAA users. The SPSS datafile lists the questions and the verbalizations coresponding to comprehension problems and their categorization. Study 2 is an analysis of all answers provided by over 350,000 respondents during the Municipal Elections of 2014. These data are owned by VAA developer Kieskompas and therefore they have not been uplloaded. In the article we predict the answers based on linguistic characteristics of the VAA questions. I have uploaded the categorization of the 1020 questions.

The central aim in our NWO 'Comprehensible Language' project (2012-2016) was to investigate to what extent Voting Advice Applications (VAAs) intentionally and unintentionally affect political knowledge and political attitudes. In this article, we present an overview of four years of research. First, we investigated reasons for use of VAAs, distinguishing three types of users: checkers (well-informed, enjoying to check the VAA), seekers (looking for political information to base their vote on) and doubters (looking for information but cynical about politics). The proportions of these groups differ for first vs. second order elections. Second, we investigated whether VAAs increase users' political knowledge. We found that users report an increase of internal efficacy due to their VAA use, but we did not find an increase in actual political knowledge. Third, a field experiment showed systematic effects of framing variation on the answers to VAA assertions, which might suggest different underlying knowledge representations. Finally, think aloud research showed that users experience considerable problems with understanding the assertions semantically and pragmatically, as well as with interpreting the results screen. Additionally, we found that users view the result screen as an end point rather than as a starting point for deliberation. We discuss some implications for theory and practice.

We analyse reaction time distributions and responses for attitudinal survey questions, which were part of a self‐administered questionnaire about medical and ethical issues. Two contrastive versions of each question were asked, whether an issue should be forbidden or whether the government should allow it. Logically, the answers to these contrastive questions should oppose, but numerous investigations have shown that they result in the so‐called forbid/allow asymmetry: respondents tend to rather say 'no' to both questions. We present a mathematical model, based on point process theory, which formalises attitude representations in memory and different stages in the response process. The data of the allow questions are used for parameter estimation, while the forbid data are used to test the predictive power of different model versions. The result is a model that describes the cognitive processes underlying the asymmetry. It indicates that the forbid/allow asymmetry is caused by the use of an increased response threshold in forbid answers, and that the asymmetry size varies due to both respondent characteristics and the issue at hand. This model is capable of simultaneously predicting the asymmetry in the reaction time distributions and in the response scores for the answering categories.

The framing of a message can affect the way people think about an issue, and the framing of attitude questions influences the opinions expressed. Current research investigated political emphasis framing in the context of Voting Advice Applications. In an online survey regarding the European Elections (2019), a conservative vs. progressive frame was manipulated across 15 questions. As the original VAA did not include introductory texts to the questions, a control condition without introduction texts was also added. Participants (N = 106) were randomly assigned to one of these three conditions. Results show that there is an effect for conservative introductions to elicit answers reflecting more progressive attitudes, but only for the group of respondents with conservative voting positions (PTV). This pattern could not be explained by political sophistication: higher political sophistication is related to a main effect of more progressive answering behaviour, but does not explain the framing effect for conservative frames in the conservative group.

How does the brain respond to statements that clash with a person's value system? We recorded event-related brain potentials while respondents from contrasting political-ethical backgrounds completed an attitude survey on drugs, medical ethics, social conduct, and other issues. Our results show that value-based disagreement is unlocked by language extremely rapidly, within 200 to 250 ms after the first word that indicates a clash with the reader's value system (e.g., "I think euthanasia is an acceptable/unacceptable…"). Furthermore, strong disagreement rapidly influences the ongoing analysis of meaning, which indicates that even very early processes in language comprehension are sensitive to a person's value system. Our results testify to rapid reciprocal links between neural systems for language and for valuation.

Voting Advice Applications (VAAs) fulfill different needs for different citizens. In national elections, the majority of users can be characterized as politically sophisticated citizens who use VAAs for entertainment purposes and confirmation of their party preference, but a significant minority uses VAAs to learn about politics and make an informed vote choice. VAAs might, however, play a different role in second-order elections, since in these elections campaign dynamics and information supply are very different. In the current research, we applied latent class analysis on user data from a widely used Dutch VAA (Kieskompas) for a supranational and several subnational elections in the Netherlands, to test if an extant typology of VAA users for national elections could be replicated. We find that the typology can be replicated for most of these elections, but also that the relative size of the groups of users differs across elections; in all second-order elections except for the provincial elections, more doubters and seekers are found relative to national elections. This suggests that VAAs are likely to have stronger mobilizing potential in these second-order elections.

Voting Advice Applications (VAAs) provide voting recommendations to millions of people. As these voting recommendations are based on users' answers to attitude questions, the framing of these questions can have far-reaching consequences. The current study reports on a field experiment in which the framing of the header above VAA statements (N = 17) was manipulated (condition 1: no header; condition 2: a right-wing header, e.g., finance; condition 3: a left-wing header, e.g., nature and environment). Visitors of a VAA developed for Utrecht, the fourth largest municipality in the Netherlands, were randomly guided to one of the versions of the tool in which the header type was varied. Results (based on Nrespondents = 27,404) show that providing a header (left-wing or right-wing) leads to more left-wing answers as compared a condition where there is no header above the attitude statement. This effect, however, is only observed for respondents with lower levels of political sophistication.

A new type of political attitude survey that has gained popularity in Europe and in the United States is the voting advice application (VAA). VAAs provide users with a voting advice based on their answers to a set of attitude questions. In the calculation of this advice, no-opinion answers are excluded. We tested the hypothesis that negative VAA questions lead to more no-opinion answers than their positive equivalents. In a field experiment, visitors (N=41,505) of a VAA developed for the municipality of Utrecht in the Netherlands, were randomly guided to one of the versions of the tool in which the polarity of 16 questions was manipulated. Results do not show an overall effect of question polarity. This overall null finding appears to be caused by contrasting effects for two subtypes of negative questions: Explicit negatives (e.g. not allow) yield more no-opinion answers than their positive counterparts (e.g. allow) do, while the reverse holds for implicit negatives (e.g. forbid).

In many countries with multiparty systems, a decline in class voting has increased volatility and the need for comprehensive information about the political landscape among voters. Voting Advice Applications (VAAs) are online tools that match users to political parties and, as such, they hold a promise of reinforcing informational transparency and democratic representation. The current research investigated whether VAAs live up to this expectation by investigating to what extent VAAs affected users' political knowledge and vote choice in the Dutch national elections of 2012. Results show that VAA users feel that the VAA improved their political knowledge. In addition, those groups of VAA users who experienced a large knowledge increase, also relatively often indicated that their vote choice had been affected. This suggests that VAAs contribute to informational transparency by increasing knowledge among a potentially wide audience, and also that VAAs might increase democratic representation to the extent that VAAs persuade people to vote for the candidate that best represents their opinions. On the other hand, we found discrepancies between behavioural and perceptual measurements of the effect of VAAs on vote choice. This raises doubts about whether VAAs shape actual voting behaviours and knowledge, or rather perceptions of that.