Social Media Monitoring for the German federal election 2017

Resource Type
Dataset : Survey and aggregate data
  • 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)
Publication Date
  • 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)
  • GESIS - Leibniz-Institut für Sozialwissenschaften Universität Koblenz Landau (Data Collector)
  • ZA:
    • Political Attitudes and Behavior
    • Political Parties, Organizations
    • Communication, Public Opinion, Media
  • CESSDA Topic Classification:
    • Elections
    • Mass political behaviour, attitudes/opinion
    • Mass media
  • Abstract

    Social 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.
Temporal Coverage
  • 2017-07-05 / 2017-09-30
Geographic Coverage
  • Germany (DE)
Sampled Universe
All 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.
Total universe/Complete enumeration; Sampling Procedure Comment: Total universe/Complete Enumeration
Time Dimension
  • Cross-section
Collection Mode
  • Field observation
  • Field observation The data was collected using Twitter’s Streaming API and via the Facebook Graph API.
Data and File Information
  • Number of Variables: 28
A 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
A - Data and documents are released for academic research and teaching.
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
Alternative Identifiers
  • ZA6926 (Type: ZA-No.)
  • 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

Update Metadata: 2021-04-07 | Issue Number: 19 | Registration Date: 2018-02-28