The 2019 European Election Study (EES) Voter Study is a post-election study, conducted in all 28 EU member states after the elections to the European Parliament were held between 23 and 26 May 2019.
The survey was conducted by Gallup International. For the first time in the history of EES, the data collection was mostly conducted online. The respondents were selected randomly from access panel databases using stratification variables, with the exception of Malta and Cyprus where a multi-stage Random Digit Dialing approach was used. In all countries the samples were stratified by gender, age, region and type of locality. The sample size is roughly 1,000 interviews in each EU member state (except Cyprus, Luxembourg and Malta where the sample size is 500). The total sample size is ~ 26,500.
The EES 2019 Voter Study questionnaire was designed by the EES 2019 Task Force, consisting of Wouter van der Brug and Sara Hobolt (co-chairs), Sebastian Adrian Popa, (treasurer), Hermann Schmitt, Eftichia Teperoglou, Ilke Toygur, Claes de Vreese and Catherine de Vries, after consultation with the wider EES user community.
The post-electoral survey consists of more than 100 items. The questionnaire includes all core traditional items included in previous EES voter studies (1989, 1994, 1999, 2004, 2009 and 2014), thus allowing for over-time as well as cross-national analysis. The study covers items on electoral behavior, such as questions on electoral participation and party choice at the EU and national level, party preferences, and propensity to support particular parties; general political attitudes; interest in politics; background characteristics such as gender, age, education, religion. Innovations in EES 2019 include batteries of questions about the consequences of Brexit and on liberal democratic attitudes. As in the case of the EES Study 2014 Voter Study, a number of the political attitude questions have the same wording as, and can be linked with, the Chapel Hill Expert Survey.
The questionnaires for the study were identical across all member states apart from differences related to party names and country-specific institutions. The translation process was supported by a network of national collaborators and we are grateful to them for their help.
We encourage users of the data to contact us should they spot any errors or anomalies in the data via email at Sebastian.Popa@ncl.ac.uk (Dr Sebastian Popa).
The EES 2019 Voters Study was generously funded by the Volkswagen Foundation. Additional grants from the MZES at the University of Mannheim and the Amsterdam Center for European Studies at the University of Amsterdam supported planning and realization of the study.
The stacked data matrix (SDM) of the 2019 European Election Studies, is a long format data matrix based on the 2019 EES voter study dataset. In this SDM each row represents the (dyadic) relationship between a voter and each relevant party in their party system at 2019 EP elections. The creation of this SDM is part of the research activities of the ProConEU project, an academic research effort analysing the enlarging gaps between proponents and opponents of the European Union (EU) in terms of party politics, civic policy, and social media communication. The data pipeline and workflow were completed between July 2021 and January 2022 (using R ≥ 4.1).
Our data covers the Twitter communication by elite political actors from all 28 EU member states during the 2019 European Parliament (EP) Election Campaign. More specifically, we focus on EP candidates from parties that received more than 2 percent of the national votes, Spitzenkandidaten (also those who did not run as a candidate on a European party list) and EU parties (not parliamentary groups). The Twitter accounts of all these EP campaign elite actors were researched during April and May 2019 by national country experts who were part of the Euromanifesto Study. The tweets sent by EP campaign elite actors were purchased from Twitter after the election. Compared to querying the Twitter API, buying the data ensures the completeness of the data. The research period is 23 April to 30 May 2019.