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Learning about the unknown Spitzenkandidaten: The role of media exposure during the 2019 European Parliament elections

European Politics
Campaign
Candidate
Internet
Communication
Public Opinion
Big Data
European Parliament
Sebastian Stier
GESIS Leibniz-Institute for the Social Sciences
Sebastian Stier
GESIS Leibniz-Institute for the Social Sciences
Simon Richter
Freie Universität Berlin

Abstract

European Parliament (EP) elections have traditionally suffered from low turnout rates, a fact that is commonly attributed to their "second-order nature". To increase the appeal of the EP elections, the establishment of the so called Spitzenkandidaten system in 2014 was supposed to personalize the vote by linking EP election results to the nomination of the European Commission presidency. In this paper, we take one step back by asking: are the European Spitzenkandidaten actually getting through to voters in the first place? Do voters learn about the European Spitzenkandidaten and can this learning be connected to specific information exposure? When answering the second question we pay special attention to the role of online news media. We draw on an integrated data set including panel survey data, self-reported media exposure measures, a passive tracking of web browsing behavior and a web crawling of the actual content seen. 1,472 German respondents participated in a web tracking study and two survey panel waves in which they were asked to link the Spitzenkandidaten to their respective European party group/national party. A validation drawing on data from the European Election Study where the same recall questions and other covariates were also implemented confirms that the sample has a high external validity. The main independent variables are self-reported offline media exposure measures and searches for the full names of the Spitzenkandidaten (e.g., "manfred weber") in the texts of the URLs visited by study participants. Learning about a candidate's party (measured in W2) is modeled as a function of a respondent's offline and online news media use, a lagged dependent variable measuring previous levels of knowledge about the candidate's party (measured in W1) and a host of confounders. The findings show that German voters indeed learned about the Spitzenkandidaten during the 2019 EP election campaign and that learning processes can be linked to news exposure offline and online. While learning was limited and unevenly distributed among candidates, exposure to general offline news and candidate-specific online news helped to acquire knowledge. The findings imply that as voters learn about the Spitzenkandidaten once they are exposed to them, their campaign platform should be expanded in order to realize substantial electoral effects. More generally, the direct observation of online behavior provides evidence for a key assumption in most observational media effects studies, that was, however, never actually tested: getting exposed to articles about specific politicians actually improves knowledge about these actors.