TikTok reveals some of the secrets, and blind spots, of its recommendation algorithm
Illustration by Alex Castro / The Verge
Like many social media platforms and apps, TikTok feeds are built using a recommendation algorithm that uses a number of tools and factors to personalize it for each person. Now, TikTok has published a new blog post explaining how its recommendation feed works, and it includes tips for personalizing the feed to avoid being served random videos you might not be interested in.
TikTok’s recommendation algorithm is built around input factors in a way somewhat similar to the way YouTube measures and monitors engagement. The way people interact with the app affects the recommendations served, including posting a comment or following an account. If someone only follows cute animal accounts, and solely double taps to like or comments on videos...