GESIS - DBK - ZA6926
 

ZA6926: Social Media Monitoring for the German federal election 2017

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ZA6926 Downloads and Data Access

List of Files

List of Files
 

Datasets

  • ZA6926_data_v1-0-0.csv.zip (Dataset) 117 MBytes
  • ZA6926_data_v1-0-0.dta.zip (Dataset) 117 MBytes
  • ZA6926_data_v1-0-0.sav.zip (Dataset) 132 MBytes

Codebooks

  • ZA6926_cod.pdf (Codebook) 430 KBytes

Other Documents

  • ZA6926_r.pdf (Report) 2 MBytes
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Bibliographic Citation

Citation Citation Stier, Sebastian; Bleier, Arnim; Bonart, Malte; Mörsheim, Fabian; Bohlouli, Mahdi; Nizhegorodov, Margarita; Posch, Lisa; Maier, Jürgen; Rothmund, Tobias; Staab, Steffen (2018): Social Media Monitoring for the German federal election 2017. GESIS Data Archive, Cologne. ZA6926 Data file Version 1.0.0, https://doi.org/10.4232/1.12992
Study No.ZA6926
TitleSocial Media Monitoring for the German federal election 2017
Current Version1.0.0, 2018-2-28, https://doi.org/10.4232/1.12992
Date of Collection05.07.2017 - 30.09.2017
Principal Investigator/ Authoring Entity, Institution
  • Stier, Sebastian - GESIS – Leibniz-Institut für Sozialwissenschaften
  • Bleier, Arnim - GESIS – Leibniz-Institut für Sozialwissenschaften
  • Bonart, Malte - GESIS – Leibniz-Institut für Sozialwissenschaften
  • Mörsheim, Fabian - Universität Koblenz-Landau
  • Bohlouli, Mahdi - Universität Koblenz-Landau
  • Nizhegorodov, Margarita - GESIS – Leibniz-Institut für Sozialwissenschaften
  • Posch, Lisa - GESIS – Leibniz-Institut für Sozialwissenschaften
  • Maier, Jürgen - Universität Koblenz-Landau
  • Rothmund, Tobias - Universität Koblenz-Landau
  • Staab, Steffen - Universität Koblenz-Landau
Contributor, Institution, Role
  • Stier, Sebastian - GESIS - Other
  • Bleier, Arnim - GESIS - Researcher
  • Bonart, Malte - GESIS - Researcher
  • Mörsheim, Fabian - University of Koblenz-Landau - Researcher
  • Bohlouli, Mahdi - University of Koblenz-Landau - Researcher
  • Nizhegorodov, Margarita - GESIS - Researcher
  • Posch, Lisa - GESIS - Researcher
  • Maier, Jürgen - University of Koblenz-Landau - Researcher
  • Rothmund, Tobias - University of Koblenz-Landau - Researcher
  • Staab, Steffen - University of Koblenz-Landau - Researcher

Content

AbstractSocial Media Monitoring of the German Federal Election Campaign 2017 This dataset contains results from the social media monitoring of Facebook and Twitter for the German federal election campaign 2017. The project collected the tweets and Facebook posts of political candidates and organizations and the engagement of users with these contents – retweets and @-mentions on Twitter, comments, shares and likes on Facebook. Finally, all messages on Twitter containing at least one keyword denoting central political topics were collected. All data was publicly available at the time of data collection. The collected data is proprietary and owned by Facebook and Twitter. Due to this and with respect to privacy restrictions, only the following aspects of the data can be shared: (1) A list of all candidates that were considered in the project, their key attributes and the identification of their respective Twitter accounts and Facebook pages. Candidate dataset: Full surname, all first names of the candidate; academic title and name pre- or suffixes (if they exist); URL of the first Facebook account; URL of the second Facebook account; URL of the Twitter account; candidate is placed on a party list; candidate’s place on the party list; candidate is a direct candidate in one of the constituencies; official number and official name of the constituency in which the candidate is running for a direct mandate; state; candidate is a member of the federal parliament (Bundestag); party of the candidate; sex, age (year of birth); place of residence; place of birth; profession. Additionally coded was: unique ID. (2) Lists of organizations relevant during an election campaign, i.e. political parties and important gatekeepers, along with their respective Twitter and Facebook accounts. (3) A list of tweet IDs which can be used to retrieve the tweets we collected during our research period.
Categories Categories
  • Political Parties, Organizations
  • Political Attitudes and Behavior
  • Communication, Public Opinion, Media
Topics Topics
  • 11.7 Elections
  • 11.5 Mass political behaviour, attitudes/opinion
  • 9.2 Mass media

Methodology

Geographic Coverage
  • Germany (DE)
UniverseAll publicly available political communication related to the Bundestagswahl 2017 on Facebook and Twitter defined by three target concepts: (1) politicians, here Facebook pages and Twitter accounts of candidates in the election campaign, (2) Facebook pages and Twitter accounts of political parties and gatekeepers such as media organizations, and (3) keywords denoting central political topics on Twitter.
Analysis Unit Analysis Unit
  • Text Unit
Sampling Procedure Sampling Procedure
  • Total universe/Complete enumeration
Total universe/Complete Enumeration
Mode of Collection Mode of Collection
  • Field observation
Field observation The data was collected using Twitter’s Streaming API and via the Facebook Graph API.
Time Method Time Method
  • Cross-section
Kind of Data Kind of Data
  • Text
  • Numeric
Data CollectorGESIS - Leibniz-Institut für Sozialwissenschaften Universität Koblenz Landau
Date of Collection
  • 05.07.2017 - 30.09.2017

Errata & Versions

VersionDate, Name, DOI
1.0.0 (current version)2018-2-28 first archive edition https://doi.org/10.4232/1.12992
Errata in current version
none
Version changes

Further Remarks

NotesA project report elaborating on target concepts, selection methods and the techniques used for data collection is published as ´Systematically Monitoring Social Media: The case of the German federal election 2017´ in GESIS Papers 2018|04
Number of Units: 3392
Number of Variables: 28
Data Type: CSV
Analysis System(s): SPSS, Stata, CSV

Publications

Publications
  • Stier, Sebastian; Bleier, Arnim; Bonart, Malte; Mörsheim, Fabian; Bohlouli, Mahdi; Nizhegorodov, Margarita; Posch, Lisa; Maier, Jürgen; Rothmund, Tobias; Staab, Steffen (2018): Systematically monitoring social media: The case of the German federal election 2017. GESIS Papers 2018|4
Relevant full texts
from SSOAR (automatically assigned)

Groups

Groups
  • German Federal Election Studies
    The data base consists of one-off surveys, panel surveys, and cumulated surveys. It comprises representative polls for all German federal elections since 1949.
    Further studies are listed under GLES (German Longitudinal Election Study).
  • Social Media Data