The EPINetz Twitter Politicians Dataset 2021. A New Resource for the Study of the German Twittersphere and Its Application for the 2021 Federal Elections.

Data Election campaigns Germany Political communication Political representatives Social Media

Journal

Politische Vierteljahresschrift
ISSN: 0032-3470
Titre abrégé: Polit Vierteljahresschr
Pays: Germany
ID NLM: 100969875

Informations de publication

Date de publication:
2022
Historique:
received: 02 03 2022
revised: 19 05 2022
accepted: 19 05 2022
pubmed: 23 6 2022
medline: 23 6 2022
entrez: 22 6 2022
Statut: ppublish

Résumé

This research note introduces the EPINetz Twitter Politicians Dataset, a comprehensive dataset of 2449 Twitter accounts of German parliamentarians, minsters, state secretaries, parties, and ministries on a state, federal, and European Union level for the year 2021. This hand-curated dataset not only provides up-to-date information on elected officials, but it also includes additional variables such as their party affiliation, age, and gender. Furthermore, it provides linkages to additional data sources by providing the accounts' Wikidata and Abgeordnetenwatch (Parliamentwatch) IDs. While it does not provide actual tweet data, the dataset will be a valuable resource for researchers by providing easy access to elected German politicians. We demonstrate some of the dataset's uses with an analysis of the 2021 German Federal Elections. The full dataset can be accessed via 10.7802/2415. The online version of this article (10.1007/s11615-022-00405-7) contains supplementary material, which is available to authorized users. Die Research Note stellt den

Autres résumés

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Identifiants

pubmed: 35730060
doi: 10.1007/s11615-022-00405-7
pii: 405
pmc: PMC9199468
doi:

Types de publication

Journal Article

Langues

eng

Pagination

529-547

Informations de copyright

© The Author(s) 2022.

Déclaration de conflit d'intérêts

Conflict of interestT. König, W.J. Schünemann, A. Brand, J. Freyberg, and M. Gertz declare that they have no competing interests.

Auteurs

Tim König (T)

Institute of Social Sciences, University of Hildesheim, Hildesheim, Germany.

Wolf J Schünemann (WJ)

Institute of Social Sciences, University of Hildesheim, Hildesheim, Germany.

Alexander Brand (A)

Institute of Social Sciences, University of Hildesheim, Hildesheim, Germany.

Julian Freyberg (J)

Institute of Computer Science, Heidelberg University, Heidelberg, Germany.

Michael Gertz (M)

Institute of Computer Science, Heidelberg University, Heidelberg, Germany.

Classifications MeSH