GESIS - DBK - ZA5710
 

ZA5710: TV Debate Analysis, Content Analysis (GLES 2013)

Downloads and Data Access


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ZA5710 Downloads and Data Access

List of Files

List of Files
 

Datasets

  • ZA5710_missing_v2-2-0.do (Dataset) 2 KBytes
  • ZA5710_v2-2-0.dta (Dataset Stata) 121 KBytes
  • ZA5710_v2-2-0.sav (Dataset SPSS) 162 KBytes
  • ZA5710_v2-2-0_open-ended.csv (Dataset) 114 KBytes

Codebooks

  • ZA5710_cod.pdf (Codebook) 540 KBytes

Other Documents

  • ZA5709-12_sb.pdf (Study Description) 593 KBytes
  • ZA5710_Transkript.pdf (Other Document) 808 KBytes
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Bibliographic Citation

Citation Citation GLES (2018): TV Debate Analysis, Content Analysis (GLES 2013). GESIS Data Archive, Cologne. ZA5710 Data file Version 2.2.0, https://doi.org/10.4232/1.13203
Study No.ZA5710
TitleTV Debate Analysis, Content Analysis (GLES 2013)
Current Version2.2.0, 2018-12-12, https://doi.org/10.4232/1.13203
Date of Collection01.09.2013 - 01.09.2013
Principal Investigator/ Authoring Entity, Institution
  • Rattinger, Hans - Universität Mannheim
  • Roßteutscher, Sigrid - Universität Frankfurt
  • Schmitt-Beck, Rüdiger - Universität Mannheim
  • Weßels, Bernhard - Wissenschaftszentrum Berlin für Sozialforschung
  • Wolf, Christof - GESIS - Leibniz-Institut für Sozialwissenschaften
Contributor, Institution, Role
  • Faas, Thorsten - Universität Mainz - ProjectLeader
  • Maier, Jürgen - Universität Koblenz-Landau - ProjectLeader
  • Maier, Michaela - Universität Koblenz-Landau - ProjectLeader
  • Blumenberg, Manuela - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator
  • Kaukal, Malte - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator
  • Kratz, Sophia - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator

Content

Topics Topics
  • 9.2 Mass media
  • 11.7 Elections

Methodology

Geographic Coverage
  • Germany (DE)
UniversePeople eligible to vote at the federal election 2013
Analysis Unit Analysis Unit
  • Text Unit
Sampling Procedure Sampling Procedure
  • Non-probability: Purposive
Mode of Collection Mode of Collection
  • Content coding
Time Method Time Method
  • Longitudinal: Trend/Repeated cross-section
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorThis study was conducted by Prof. Dr. Thorsten Faas (Universität Mainz), Prof. Dr. Jürgen Maier (Universität Koblenz-Landau) and Prof. Dr. Michaela Maier (Universität Koblenz-Landau) at Koblenz, Landau/Pfalz und Mainz.
Date of Collection
  • 01.09.2013

Errata & Versions

VersionDate, Name, DOI
2.2.0 (current version)2018-12-12 Release2-2-0 https://doi.org/10.4232/1.13203
2.1.02017-4-25 Release2-1-0 https://doi.org/10.4232/1.12770
2.0.02014-12-17 Release2-0-0 https://doi.org/10.4232/1.12143
1.0.02014-6-13 Release1-0-0 https://doi.org/10.4232/1.11943
Errata in current version
none
Version changes
Changes between version 2.2.0 and it's previous version
DateSubjectDescriptionCorrection Description
2018-12-12Recoding of variable v7 for respondents with identifiers v1 = 192, 479 and 4802018-12-12
Changes between version 2.1.0 and it's previous version
DateSubjectDescriptionCorrection Description
2017-4-25Recoding: v4,v6,v8Variable v4, v6 and v8 have been recoded for ID (v1) 318,648,650.2017-4-25
Changes between version 2.0.0 and it's previous version
DateSubjectDescriptionCorrection Description
2014-12-17The value label of code 9 in variable v28 and v35 has been renamed.2014-12-17
2014-12-17The duration of the given statements (v8) was recalculated completely. Thus, several time points in minutes of the statements (v6) have been corrected.2014-12-17
2014-12-17Several statements have been recoded in aspect of the strategy (v12), regarding speaker (v12) and the type of statement (v33).2014-12-17

Further Remarks

Links
Number of Units: 877
Number of Variables: 37
Analysis System(s): SPSS, Stata

Publications

Relevant full texts
from SSOAR (automatically assigned)

Groups

Research Data Centre
Groups
  •  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.