GESIS - DBK - ZA6812

ZA6812: TV Debate Analysis, Real-Time-Response Data TV Debate (dial) (GLES 2017)

Downloads and Data Access

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ZA6812 Downloads and Data Access

List of Files

List of Files


  • ZA6812_v1-0-0.dta (Dataset Stata) 2 MBytes
  • ZA6812_v1-0-0.sav (Dataset SPSS) 2 MBytes

Other Documents

  • ZA6810ff_sb.pdf (Study Description) 880 KBytes
Availability Availability A - Data and documents are released for academic research and teaching.
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Bibliographic Citation

Citation Citation GLES (2019): TV Debate Analysis, Real-Time-Response Data TV Debate (dial) (GLES 2017). GESIS Data Archive, Cologne. ZA6812 Data file Version 1.0.0,
Study No.ZA6812
TitleTV Debate Analysis, Real-Time-Response Data TV Debate (dial) (GLES 2017)
Current Version1.0.0, 2019-4-8,
Date of Collection03.09.2017 - 03.09.2017
Principal Investigator/ Authoring Entity, Institution
  • Roßteutscher, Sigrid - Universität Frankfurt
  • Schmitt-Beck, Rüdiger - Universität Mannheim
  • Schoen, Harald - Universität Mannheim
  • Weßels, Bernhard - Wissenschaftszentrum Berlin für Sozialforschung
  • Wolf, Christof - GESIS – Leibniz-Institut für Sozialwissenschaften
Contributor, Institution, Role
  • Faas, Thorsten - Freie Universität Berlin - ProjectLeader
  • Maier, Jürgen - Universität Koblenz-Landau - ProjectLeader
  • Maier, Michaela - Universität Koblenz-Landau - ProjectLeader
  • Jungmann, Nils - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator


Geographic Coverage
  • Germany (DE)
UniverseGerman citizens who were eligible to vote in the 2017 German federal election at the time of the survey
Analysis Unit Analysis Unit
  • Individual
Sampling Procedure Sampling Procedure
  • Non-probability: Availability
  • Non-probability: Quota
Mode of Collection Mode of Collection
  • Measurements and tests
Time Method Time Method
  • Time series: Continuous
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorThis study was conducted by Prof. Dr. Thorsten Faas (Johannes Gutenberg University Mainz), Prof. Dr. Jürgen Maier (University of Koblenz-Landau) and Prof. Dr. Michaela Maier (University of Koblenz-Landau) at Mainz and Landau.
Date of Collection
  • 03.09.2017

Errata & Versions

VersionDate, Name, DOI
1.0.0 (current version)2019-4-8 first archive edition
Errata in current version
Version changes

Further Remarks

Number of Units: 138
Number of Variables: 5862
Analysis System(s): SPSS, Stata


Relevant full texts
from SSOAR (automatically assigned)


Research Data Centre
  •  German Longitudinal Election Study (GLES)
    The German Longitudinal Election Study (GLES) is a DFG-funded project which made its debut just prior to the 2009 federal election. GLES is the largest and most ambitious election study held so far in Germany. Although the initial mandate is to examine and analyse the electorate for three consecutive elections, the aspired goal is to integrate the project within GESIS as an institutionalized election study after the federal election of 2017, and hence to make it a permanent study.