Beyond Young, Highly Educated Males: A Typology of VAA Users

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.

[1]  Claes H. de Vreese,et al.  The differential role of the media as an agent of political socialization in Europe , 2013 .

[2]  R. Niemi,et al.  Measuring Internal Political Efficacy in the 1988 National Election Study , 1991, American Political Science Review.

[3]  Alexander H. Trechsel,et al.  Voting Advice Applications: How Useful and for Whom? , 2014 .

[4]  William P. Eveland,et al.  Education, Need for Cognition, and Campaign Interest as Moderators of News Effects on Political Knowledge: An Analysis of the Knowledge Gap , 2005 .

[5]  M. L. Adriaansen,et al.  UvA-DARE (Digital Academic Repository) Versatile citizens: media reporting, political cynicism and voter behavior , 2011 .

[6]  Late-deciding voters in presidential elections , 1994 .

[7]  Thomas Vitiello,et al.  Do voters follow the recommendations of voter advice application websites? A study of the effects of kieskompas.nl on its users’ vote choices in the 2010 Dutch legislative elections , 2014 .

[8]  Marcel Boogers,et al.  Surfing citizens and floating voters: Results of an online survey of visitors to political web sites during the Dutch 2002 General Elections , 2003, Inf. Polity.

[9]  Wouter Teepe,et al.  Party profiles on the web: an analysis of the logfiles of non-partisan interactive political internet sites in the 2003 and 2004 election campaigns in Belgium , 2007, New Media Soc..

[10]  M. Gallagher Do political campaigns matter? Campaign effects in elections and referendums , 2003 .

[11]  A.M.J. Derks Post-broadcast democracy: How media choice increases inequality in political involvement and polarizes elections , 2009 .

[12]  J. Hagenaars,et al.  Applied Latent Class Analysis , 2003 .

[13]  K. Kenski,et al.  Connections Between Internet Use and Political Efficacy, Knowledge, and Participation , 2006 .

[14]  G. Voerman,et al.  Surfing citizens and floating voters , 2003 .

[15]  P. Dumont,et al.  Smartvote.lu: usage and impact of the first VAA in Luxembourg , 2012 .

[16]  Kristjan Vassil Role of Self Selection in Estimating the Effects of Voting Advice Applications: Empirical Evidence on the Basis of Swiss Smartvote Data , 2011 .

[17]  B. Muthén,et al.  Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study , 2007 .

[18]  Clarissa C. David Learning Political Information From the News: A Closer Look at the Role of Motivation , 2009 .

[19]  Ruth Dassonneville Electoral volatility, political sophistication, trust and efficacy: A study on changes in voter preferences during the Belgian regional elections of 2009 , 2012 .

[20]  E. Katz,et al.  Uses and Gratifications Research , 2019, The International Encyclopedia of Journalism Studies.

[21]  Jan Fivaz,et al.  Impact of Voting Advice Applications (VAAs) on Voter Turnout and Their Potential Use for Civic Education , 2010 .

[22]  G. Celeux,et al.  An entropy criterion for assessing the number of clusters in a mixture model , 1996 .

[23]  Outi Ruusuvirta,et al.  Do online vote selectors influence electoral participation and the directionof the vote , 2009 .

[24]  Delia Baldassarri,et al.  Voter heuristics and political cognition in Italy: An empirical typology , 2006 .

[25]  Kevin M. Beaver,et al.  Toward a Quantitative Typology of Burglars: A Latent Profile Analysis of Career Offenders , 2008, Journal of forensic sciences.

[26]  J. Tedesco,et al.  Introduction Political Information Efficacy and Young Voters , 2007 .

[27]  R. Schmitt-Beck,et al.  Why Voters Decide Late: A Simultaneous Test of Old and New Hypotheses at the 2005 and 2009 German Federal Elections , 2012 .

[28]  Daniel Manrique-Vallier,et al.  A Mixed Membership Approach to Political Ideology , 2014, Handbook of Mixed Membership Models and Their Applications.

[29]  Galen A. Irwin,et al.  What are they Waiting for? Strategic Information for Late Deciding Voters , 2008 .

[30]  H. V. D. Kolk,et al.  Twijfelen en kiezen , 2007 .

[31]  Stefaan Walgrave,et al.  ‘Do the Vote Test’: The Electoral Effects of a Popular Vote Advice Application at the 2004 Belgian Elections , 2008 .

[32]  André Blais,et al.  Time-of-voting decision and susceptibility to campaign effects , 2004 .

[33]  Michael E. Morrell Survey and Experimental Evidence for a Reliable and Valid Measure of Internal Political Efficacy , 2003 .

[34]  Thomas J. Johnson,et al.  A Web for all reasons: uses and gratifications of Internet components for political information , 2004, Telematics Informatics.

[35]  Claes H. de Vreese,et al.  News matters: Influences on the vote in the Danish 2000 euro referendum campaign , 2004 .

[36]  P. Mair Electoral Volatility and the Dutch Party System: A Comparative Perspective , 2008 .

[37]  T. V. D. van der Meer,et al.  Are volatile voters erratic, whimsical or seriously picky? A panel study of 58 waves into the nature of electoral volatility (The Netherlands 2006–2010) , 2015 .

[38]  Petter Bae Brandtzæg,et al.  Towards a unified Media-User Typology (MUT): A meta-analysis and review of the research literature on media-user typologies , 2010, Comput. Hum. Behav..

[39]  Diego Garzia,et al.  Voting Advice Applications under review: the state of research , 2012 .

[40]  Diego Garzia,et al.  Matching Voters with Parties and Candidates: Voting Advice Applications in a Comparative Perspective , 2014 .

[41]  Thomas J. Johnson,et al.  Online and in the Know: Uses and Gratifications of the Web for Political Information , 2002 .

[42]  Martin Schultze,et al.  Voting Advice Applications and their effect on voter turnout: the case of the German Wahl–O–Mat , 2012 .

[43]  J. Cacioppo,et al.  The need for cognition. , 1982 .

[44]  Marco Lisi,et al.  Voting Advice Applications in Europe: The State of the Art , 2010 .

[45]  Edoardo M. Airoldi,et al.  A Mixed Membership Approach to the Assessment of Political Ideology from Survey Responses , 2014 .

[46]  Liesbet van Zoonen,et al.  Internet Use and Political Participation: Reflections on the Mobilization/Normalization Controversy , 2011, Inf. Soc..

[47]  Thomas Vitiello,et al.  The practicalities of issuing vote advice: a new methodology for profiling and matching , 2012 .