Matching Voters with Parties and Candidates: Voting Advice Applications in a Comparative Perspective [Paperback]

Against this background, Matching Voters With Parties and Candidates aims first at a comprehensive overview of the VAA phenomenon in a truly comparative perspective.Voting Advice Applications  VAAs  have become a widespread online feature of electoral campaigns in Europe, attracting growing interest from social and political scientists. But until now, there has been no systematic and reliable comparative assessment of these tools. Previously published research on VAAs has resulted almost exclusively in national case studies. This lack of an integrated framework for analysis has made research on VAAs unable to serve the scientific goal of systematic knowledge accumulation. Against this background, Matching Voters With Parties and Candidates aims first at a comprehensive overview of the VAA phenomenon in a truly comparative perspective. Featuring the biggest number of European experts on the topic ever assembled, the book answers a number of open questions and addresses debates in VAA research. It also aims to bridge the gap between VAA research and related fields of political science.ContentsList of Figures and Tables viiContributors xiAcknowledgements xvChapter One  Voting Advice Applications in a Comparative Perspective:An IntroductionStefan Marschall and Diego Garzia 1Chapter Two  The Content and Formulation of Statements in VotingAdvice Applications: A Comparative Analysis of 26 VAAsKirsten Van Camp, Jonas Lefevere and Stefaan Walgrave 11Chapter Three  Comparing Methods for Estimating Parties Positions inVoting Advice ApplicationsKostas Gemenis and Carolien van Ham 33Chapter Four  Whats Behind a Matching Algorithm? A CriticalAssessment of How Voting Advice Applications Produce VotingRecommendationsFernando Mendez 49Chapter Five  Voting Advice Applications as Campaign Actors:Mapping VAAs Interactions with Parties, Media and VotersAndr? Krouwel, Thomas Vitiello and Matthew Wall 67Chapter Six  Data Quality and Data CleaningIoannis Andreadis 79Chapter SevelÃ%