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gptforfree/DataTube

DataTube DataTube is a curated dataset of YouTube channels derived from Wikidata. The dataset was created by querying Wikidata for entities identified as YouTube channels and collecting available channel identifiers and audience-related statistics. The resulting data was cleaned and consolidated so that each YouTube channel appears once. Dataset contents Each row represents one unique YouTube channel. Column Description channellabel Human-readable… See the full description on the dataset page: https://huggingface.co/datasets/gptforfree/DataTube.

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DataTube

DataTube is a curated dataset of YouTube channels derived from Wikidata.

The dataset was created by querying Wikidata for entities identified as YouTube channels and collecting available channel identifiers and audience-related statistics. The resulting data was cleaned and consolidated so that each YouTube channel appears once.

Dataset contents

Each row represents one unique YouTube channel.

Column Description ---------------- --------------------------------------------------- channellabel Human-readable channel/entity label from Wikidata channelid YouTube channel ID (Wikidata property P2397) subscribers Available subscriber count followers Available social-media follower count views Available viewers/listeners count

Missing numerical values are represented as none.

Dataset statistics

  • —1,565 unique YouTube channels
  • —One row per channel
  • —Source: Wikidata
  • —Format: CSV

Source

The underlying data comes from Wikidata, the free collaborative knowledge base.

YouTube channel IDs are based on Wikidata property P2397 (YouTube channel ID). Wikidata defines this property as the identifier of a YouTube channel and documents the expected channel-ID format.

The dataset is a processed extract: the original Wikidata results were queried, deduplicated, and cleaned for use as a standalone tabular dataset.

Query and processing

The original Wikidata query retrieved YouTube channels together with available audience statistics. Because Wikidata can contain multiple historical statements for the same channel, the raw query output contained repeated channels. DataTube consolidates these observations into one row per YouTube channel ID and retains the most recent available value for each audience metric.

License

The structured data in Wikidata's main, Property, Lexeme, and EntitySchema namespaces is released under the Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication.

Accordingly, this dataset is released under CC0 1.0 for the Wikidata-derived data.

Wikidata licensing information: https://www.wikidata.org/wiki/Wikidata:Licensing

Wikidata copyright policy: https://www.wikidata.org/wiki/Wikidata:Copyright

Important notes

  • —Subscriber, follower, and view-related values are Wikidata-sourced observations, not necessarily live YouTube statistics.
  • —Audience statistics can become outdated as channel metrics change.
  • —followers and views should not automatically be interpreted as YouTube subscriber counts or YouTube video views; their meanings follow the corresponding Wikidata properties.
  • —A value of none means that no usable numeric value was available in the source data used to create this dataset.
  • —DataTube is an independent dataset and is not affiliated with Wikidata, Wikimedia Foundation, or YouTube.

Intended uses

DataTube may be useful for:

  • —YouTube channel discovery
  • —Dataset exploration and visualization
  • —Knowledge-graph research
  • —Entity resolution and linking
  • —Social-media research
  • —Machine-learning experiments
  • —Analysis of online media ecosystems

Citation

If you use DataTube, please cite the dataset and acknowledge Wikidata as the underlying source.

DataTube --- A cleaned dataset of YouTube channels derived from Wikidata.

For the underlying data source, see the Wikidata project and its licensing documentation.

Disclaimer

This dataset is provided as-is. Channel metadata and audience statistics may be incomplete, stale, or subject to changes in Wikidata. Users should verify important information against current sources before relying on it.