Understanding YouTube Communities via Subscription-based Channel Embeddings

Understand

YouTube is an important source of news and entertainment worldwide, but the scale makes it challenging to study the ideas and topics being discussed on the platform.

• This paper presents new methods to discover and classify YouTube channels which enable the analysis of communities and categories on the platform using orders of magnitude more channels than have been used in previous studies.
• Instead of using channel and video data as features for classification as other researchers have, these methods use a self-supervised learning approach that leverages the public subscription pages of commenters.
• We test the classification method on the task of predicting the political lean of YouTube news channels and find that it outperforms the previous best model on the task.