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metadata language: German English

Campaign Media Content Analysis, TV (GLES 2009)

Version
1.2.0
Resource Type
Dataset
Creator
  • Rattinger, Hans (Universität Mannheim)
  • Roßteutscher, Sigrid (Universität Frankfurt)
  • Schmitt-Beck, Rüdiger (Universität Mannheim)
  • Weßels, Bernhard (Wissenschaftszentrum Berlin für Sozialforschung)
  • Krewel, Mona (Universität Mannheim)
Other Title
  • German Longitudinal Election Study (Alternative Title)
Publication Date
2015-04-13
Contributor
  • GöfaK Medienforschung, Potsdam (Data Collector)
Language
German
Classification
  • ZA:
    • Political Attitudes and Behavior
Description
  • Abstract

    Content analytical coverage of TV news.
Temporal Coverage
  • 2009-06-28 / 2009-09-26
Geographic Coverage
  • Germany (DE)
Sampled Universe
„Tagesschau“ (ARD), „Heute“ (ZDF), „RTL aktuell“ (RTL) and „News“ (SAT1).
Collection Mode
  • Content Analysis of TV news.
Data and File Information
  • Unit Type: Individual
    Number of Units: 6212
    Number of Variables: 115
Note
The documented study was conducted in the context of the German Longitudinal Election Study (GLES), 2009.
Availability
Download
A - Data and documents are released for academic research and teaching.
Rights
All metadata from GESIS DBK are available free of restriction under the Creative Commons CC0 1.0 Universal Public Domain Dedication. However, GESIS requests that you actively acknowledge and give attribution to all metadata sources, such as the data providers and any data aggregators, including GESIS. For further information see https://dbk.gesis.org/dbksearch/guidelines.asp
Alternative Identifiers
  • ZA5306 (Type: ZA-No.)
  • WAHLEN (Type: FDZ)
Relations
  • Is new version of
    DOI: 10.4232/1.11401
  • Is new version of
    DOI: 10.4232/1.10366

Update Metadata: 2017-12-28 | Issue Number: 6 | Registration Date: 2015-04-14

Rattinger, Hans; Roßteutscher, Sigrid; Schmitt-Beck, Rüdiger; Weßels, Bernhard; Krewel, Mona (2015): Wahlkampf-Medieninhaltsanalyse, Fernsehen (GLES 2009). Version: 1.2.0. GESIS Datenarchiv. Dataset. https://doi.org/10.4232/1.12211