2026-04-15T07:48:38Z
https://datacatalogue.cessda.eu/oai-pmh/v0/oai
ad3f1b909f3bd58af9f0a2fecd8d87bc718e79cc15bdf1ea24ab5b03ab219a6e
2025-10-01T03:06:45Z
language:enopenaire_data
DDI study level documentation for study 10.7802/2863 News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023
News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023
News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023
10.7802/286310.7802/286310.7802/286310.7802/2863
Wedel, Lion
Wedel, Lion
Mayer, Anna-Theresa
Mayer, Anna-Theresa
Batzner, Jan
Batzner, Jan
Hendrickx, Jonathan
Hendrickx, Jonathan
[Federal Ministry of Education and Research of Germany (BMBF) under grant no. 16DII131 (Weizenbaum-Institut für die vernetzte Gesellschaft - Das Deutsche Internet-Institut)]
GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften
journalismjournalistsocial medianewsnews value theoryjournalismjournalistsocial medianewsnews value theory
TikTok is developing into a key platform for news, advertising, politics, online shopping, and entertainment in Germany, with over 20 million monthly users. Especially among young people, TikTok plays an increasing role in their information environment. We provide a human-coded dataset of over 4,000 TikTok videos from German-speaking news outlets from 2023. The coding includes descriptive variables of the videos (e.g., visual style, text overlays, and audio presence) and theory-derived concepts from the journalism sciences (e.g., news values). This dataset consists of every second video published in 2023 by major news outlets active on TikTok from Germany, Austria, and Switzerland. The data collection was facilitated with the official TikTok API in January 2024. The manual coding took place between September 2024 and December 2024. For a detailed description of the data collection, validation, annotation and descriptive analysis, please refer to: Mayer, A.-T., Wedel, L., Batzner, J., Hendrickx, J., Bremer, E., Iwan, A., Stocker, V., & Ohme, J. (2025). News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023. Proceedings of the Nineteenth International AAAI Conference on Web and Social Media, 19, forthcoming.TikTok is developing into a key platform for news, advertising, politics, online shopping, and entertainment in Germany, with over 20 million monthly users. Especially among young people, TikTok plays an increasing role in their information environment. We provide a human-coded dataset of over 4,000 TikTok videos from German-speaking news outlets from 2023. The coding includes descriptive variables of the videos (e.g., visual style, text overlays, and audio presence) and theory-derived concepts from the journalism sciences (e.g., news values). This dataset consists of every second video published in 2023 by major news outlets active on TikTok from Germany, Austria, and Switzerland. The data collection was facilitated with the official TikTok API in January 2024. The manual coding took place between September 2024 and December 2024. For a detailed description of the data collection, validation, annotation and descriptive analysis, please refer to: Mayer, A.-T., Wedel, L., Batzner, J., Hendrickx, J., Bremer, E., Iwan, A., Stocker, V., & Ohme, J. (2025). News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023. Proceedings of the Nineteenth International AAAI Conference on Web and Social Media, 19, forthcoming.
GermanyGermanySwitzerlandSwitzerlandAustriaAustria
Every second video published in 2023 by the most relevant traditional news media accounts on TikTok from Germany, Switzerland, and Austria.
Time seriesTimeSeriesZeitreihenTimeSeries
Non-probability Sample - Purposive SampleNon-probability Sample - Purposive Sample
RecordingRecordingAufzeichnung (mechanisch/elektronisch)Recording
Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.
CC BY-NC-SA 4.0: Attribution - NonCommercial – ShareAlike (https://creativecommons.org/licenses/by-nc-sa/4.0/deed.de)Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden.
CC BY-NC-SA 4.0: Attribution - NonCommercial – ShareAlike (https://creativecommons.org/licenses/by-nc-sa/4.0/deed.de)
http://dbkapps.gesis.org/dbkoai/oai.asp
oai:dbk.gesis.org:SDN/10.7802_2863
2025-07-15
ddi:codebook:2_5