GESIS - DBK - ZA6808
 

ZA6808: Campaign Media Content Analysis, TV (GLES 2017)

Downloads and Data Access


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ZA6808 Downloads and Data Access

List of Files

List of Files
 

Datasets

  • ZA6808_missing.do (Dataset) 2 KBytes
  • ZA6808_v1-0-0.dta (Dataset Stata) 2 MBytes
  • ZA6808_v1-0-0.sav (Dataset SPSS) 2 MBytes

Other Documents

  • ZA6808_Kurzanleitung.pdf (Other Document) 112 KBytes
  • ZA6808_mb.pdf (Method Report) 2 MBytes
  • ZA6808_mr.pdf (Method Report) 1 MByte
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Bibliographic Citation

Citation Citation GLES (2018): Campaign Media Content Analysis, TV (GLES 2017). GESIS Data Archive, Cologne. ZA6808 Data file Version 1.0.0, https://doi.org/10.4232/1.13186
Study No.ZA6808
TitleCampaign Media Content Analysis, TV (GLES 2017)
Current Version1.0.0, 2018-11-20, https://doi.org/10.4232/1.13186
Date of Collection27.06.2017 - 23.09.2017
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
  • Schmitt-Beck, Rüdiger - Universität Mannheim - ProjectLeader
  • Schackmann, Lena Marie - Universität Mannheim - ProjectManager
  • Krewel, Mona - Universität Mannheim - ProjectMember
  • Schäfer, Anne - Universität Mannheim - ProjectMember
  • Schmidt, Sebastian - Universität Mannheim - ProjectMember
  • Jungmann, Nils - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator

Methodology

Geographic Coverage
  • Germany (DE)
UniverseTV news coverage during the field period
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 CollectorUniversity of Mannheim - Chair of Political Science I
Date of Collection
  • 27.06.2017 - 23.09.2017

Errata & Versions

VersionDate, Name, DOI
1.0.0 (current version)2018-11-20 first archive edition https://doi.org/10.4232/1.13186
Errata in current version
none
Version changes

Further Remarks

Number of Units: 5151
Number of Variables: 105
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.