A categorized multimodal TikTok dataset

Wedel, Lion

A categorized multimodal TikTok dataset

dc.contributor.author	Wedel, Lion
dc.date.accessioned	2023-11-24T10:30:15Z
dc.date.available	2023-11-24T10:30:15Z
dc.date.collected	2023-07-31/2023-08-04
dc.date.issued	2023
dc.description.abstract	This dataset encompasses 11242 entries of 5137 unique videos listed between the 31st of July and the 4th of August on the TikTok explore page (https://www.tiktok.com/explore). The page was accessed via a German IP address without being logged in. The data has been collected via the 4CAT Toolkit and the Zeeschuimer browser extension. The dataset contains the category and multimodal embeddings for each video. Intended Purpose The dataset is primarily intended for proof-of-concept studies, as a toy dataset to teach or to be used for seminar papers by students. Given the lack of a clear definition for each category by TikTok, the focus of such work might be to explore those definitions or to conduct work with a focus on methods. The multimodal embeddings allow for directly applying unsupervised and supervised machine learning techniques. Contents The dataset consists of four zipped .csv files: * – metadata.zip * – text_embeddings.zip * – audio_embeddings.zip * – video_embedding.zip For further details, please consult the Data Report (datenbericht_v2.pdf).	en
dc.identifier.citation	Wedel, L. (2023). A categorized multimodal TikTok dataset [Data set]. Weizenbaum Institute. https://doi.org/10.34669/WI.RD/3
dc.identifier.uri	https://www.weizenbaum-library.de/handle/id/420
dc.language.iso	eng
dc.rights	open access
dc.rights.uri	https://creativecommons.org/licenses/by-nc/4.0/
dc.subject	TikTok
dc.subject	Machine Learning
dc.subject	Video
dc.subject	Audio
dc.title	A categorized multimodal TikTok dataset
dc.type	ResearchData
dcmi.type	Dataset
dcterms.bibliographicCitation.originalpublisherplace	Berlin
dcterms.contributor.datacollector	Wedel, Lion
local.researchgroup	Dynamiken digitaler Nachrichtenvermittlung
local.researchtopic	Digitale Märkte und Öffentlichkeiten auf Plattformen