# YouNiverse: Large-Scale Channel and Video Metadata from English-Speaking YouTube

arXiv: https://arxiv.org/abs/2012.10378 · HTML: https://mlsanity.com/paper/2012.10378/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Dec 2020.

## Built on by (most cited first, 2 of 2)

- [Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments](https://mlsanity.com/paper/2207.01504/) (2022)
- [When Jokes Cross the Line: Analyzing Regular Humor and Dark Humor in YouTube Shorts](https://mlsanity.com/paper/2606.00046/) (2026)

## Abstract (arXiv)

YouTube plays a key role in entertaining and informing people around the globe. However, studying the platform is difficult due to the lack of randomly sampled data and of systematic ways to query the platform's colossal catalog. In this paper, we present YouNiverse, a large collection of channel and video metadata from English-language YouTube. YouNiverse comprises metadata from over 136k channels and 72.9M videos published between May 2005 and October 2019, as well as channel-level time-series data with weekly subscriber and view counts. Leveraging channel ranks from socialblade.com, an online service that provides information about YouTube, we are able to assess and enhance the representativeness of the sample of channels. Additionally, the dataset also contains a table specifying which videos a set of 449M anonymous users commented on. YouNiverse, publicly available at https://doi.org/10.5281/zenodo.4650046, will empower the community to do research with and about YouTube.