Abstract
Voting Advice Applications (VAAs) are Web tools that are used to inform increasing numbers of voters during elections. This increasing usage indicates that VAAs fulfill voters’ needs, but what these needs are is unknown. Previous research has shown that such tools are primarily used by young males and highly educated citizens. This suggests that VAAs are generally used by citizens who are already well-informed about politics and may not need the assistance of a VAA to make voting decisions. To analyze the functions that VAAs have for their users, this study utilizes unique user data from a popular Dutch VAA to identify different user types according to their cognitive characteristics and motivations. A latent class analysis (LCA) resulted in three distinct user types that vary in efficacy, vote certainty, and interest: doubters, checkers, and seekers. Each group uses the VAA for different reasons at different points in time. Seekers’ use of VAAs increases as Election Day approaches; less efficacious and less certain voters are more likely to use the tool to become informed.
Notes
1. VAAs assume that users seek assistance to match their political opinions to a party platform. As Fossen, Anderson, and Tiemeijer (Citation2012) remark, however, it is more often the case that users do not hold clear opinions on many issues and rather need assistance to define their own position.
2. These categories were combined because of the low number of people in the latter category (3.8%).
3. In an alternative specification of the model, we also included the personality trait Need for Cognition (NFC; Cacioppo & Petty, Citation1982). This trait reflects the motivation to inform oneself about news and politics (David, Citation2009). We tested whether including this trait in our analyses would contribute to differentiating between those who are more fundamentally interested and those who are in need of immediate information. However, because we measured this concept using a single item (it is typically measured using at least 18 items) and the measure failed to discriminate between groups of users, we omitted it from the final model. It is unclear whether the lack of discriminatory power has a substantial meaning for the role of NFC in the typology, or alternatively, is the result of suboptimal measurement.
4. A cluster analysis (performed using Ward’s method and Gower’s similarity coefficient) showed patterns that moderately resemble the type-specific patterns identified using the LCA. However, the distribution of users across types is different. According to the cluster analysis, each type represents about 33% of the users. Membership in a cluster analysis user type was moderately correlated with LCA type membership (Cramér’s V = .35, p < .001).
Additional information
Notes on contributors
Jasper van de Pol
Jasper van de Pol is a PhD candidate at the Amsterdam School of Communication Research. His PhD project is on the uses and effects of voting advice applications.
Bregje Holleman
Bregje Holleman is an assistant professor at the Utrecht Institute of Linguistics at Utrecht University. Her research focuses on cognitive aspects of text processing, mainly in attitude surveys and in persuasive texts.
Naomi Kamoen
Naomi Kamoen is a postdoctoral scholar at the Utrecht Institute of Linguistics at Utrecht University and a teacher in the Department of Communication and Information Sciences at Tilburg University. Her research focuses on framing in voting advice applications and attitude surveys.
André Krouwel
André Krouwel is an associate professor in the Department of Communication of VU University, Amsterdam, and is the scientific director of Kieskompas. His research focuses on political parties, voters, elections and voting advice applications.
Claes de Vreese
Claes de Vreese is a professor and chair of political communication at the Amsterdam School of Communication Research at University of Amsterdam. His research interests include political journalism, media effects, public opinion, and electoral behavior in Europe.