Summary information
Study title
News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023
Creator
Wedel, Lion ( Weizenbaum Institute for the Networked Society)
Mayer, Anna-Theresa ( Weizenbaum Institute for the Networked Society)
Batzner, Jan ( Weizenbaum Institute for the Networked Society)
Hendrickx, Jonathan ( University of Copenhagen)
Study number / PID
10.7802/2819 (GESIS)
10.7802/2819 (DOI)
Data access
Information not available
Series
Not available
Abstract
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 [Forthcoming dataset paper publication].
Topics
Keywords
Methodology
Data collection period
01/01/2024 - 31/01/2024
Country
Deutschland, Schweiz, Österreich
Time dimension
Time series
Analysis unit
Not availableUniverse
Every second video published in 2023 by the most relevant traditional news media accounts on TikTok from Germany, Switzerland, and Austria.
Sampling procedure
Nicht-Wahrscheinlichkeitsauswahl - Bewusste Auswahl
Kind of data
Not availableData collection mode
Recording
Content Analysis
Access
Publisher
GESIS Data Archive for the Social Sciences
Publication year
2025
Terms of data access
Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.
CC BY-NC-SA 4.0: Namensnennung - Nicht kommerziell – Weitergabe unter gleichen Bedingungen (https://creativecommons.org/licenses/by-nc-sa/4.0/deed.de)
Related publications
Not available