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A Hugging Face repository describes a dataset of nearly 5.6 billion public TikTok videos, but it does not contain the videos themselves. It contains structured metadata and engagement counts. The dataset card gives a collection count of 5,597,462,038 videos and a snapshot date of October 3, 2026; the repository page separately reports 5,598,141,717 rows and a size of 460 GB. Those are different page-reported figures, not interchangeable counts.
What the dataset contains
The repository is a large tabular dataset, not an archive of playable TikTok clips. Its listed fields describe videos and their associated activity, allowing analysis of metadata without providing the underlying footage. The dataset card’s schema includes:
- Video IDs, posting timestamps, region and language
- Video or photo type and duration
- Captions, hashtags, mentions, on-screen text and sounds
- Advertising and branded-content flags
- TikTok Shop product and seller IDs
- Engagement counts
- Nullable flags for AI-generated content and recommendation eligibility
These fields may support large-scale metadata analysis, but the presence of a field does not guarantee that every record has a value for it.
What the counts and snapshot date mean
The Hugging Face page displays two separate figures: the dataset card describes 5,597,462,038 public videos spanning 2014 through October 2026, while the repository page reports 5,598,141,717 rows. The page also reports a size of 460 GB and gives October 3, 2026 as the snapshot date. These are repository-reported figures, not independently verified totals, and may change if the repository is updated. See the Hugging Face dataset card and repository for the current listing.
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How complete and consistent is the data?
The dataset card says older records come from an archive and may have zero or null values for some fields. It also notes that older video durations may be rounded to the nearest second. This means fields and precision can vary across the collection’s time span; a missing or zero value should not automatically be interpreted as proof that an event or attribute did not exist.
How the uploader says it was collected
In an October 2026 Reddit post, the uploader, DataShack, says the collection was built by reverse engineering TikTok’s mobile app and describes the data as public and accessible without logging in. Those are the uploader’s claims, not independently audited findings. The dataset page advertises a technical guide and source code relating to mobile API endpoints, request signing and device registration; that material does not independently establish the stated total, completeness, or continued access. The post is available at DataShack’s Reddit account.
Is it really free to use?
The dataset card displays a CC BY-NC 4.0 label and describes the dataset as free for research and personal use. It directs users seeking commercial use, creator profiles or daily updates to datasocial.ai. This is how the dataset page presents its license and offerings; the label alone does not establish rights to every underlying record or settle questions about platform terms, privacy, or other legal obligations. The TikTok Terms of Service are a relevant primary source, but the applicable questions are not resolved by the dataset page.
For anyone considering using the data, check the live dataset card and applicable terms for the intended use, especially before commercial use or handling information about creators. This is not legal advice.
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The release offers a very large, structured view of TikTok-related metadata, according to its own card and repository. It does not provide the video footage, and the listed totals and collection method have not been independently verified in the sources cited here. The uploader’s description also does not establish that TikTok approved the collection or that access will continue. The official TikTok Research API page is available, but the eligibility details needed to assess it as an alternative are not established here.
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