@dansup It seems like the other side of the equation is what data is available on each video post?

There's the internal metadata (creator, creation time, duration, camera, filters, etc.) Then attached metadata (description, hashtags, etc). A lot of recent energy has gone into determining the content via AI (what is actually inside the video/audio channels). Classifiers can also tag for emotions/sentiment.

Then it goes one step up and connects the content attributes to user votes, moderation actions, and misinformation/reporting data, to generate some sort of score (heat, excitement, or outrage). Some of these could be pre-calced during submission stage so runtime selection is faster.

An algo would crunch all these attributes into a "this person will like this clip" score.

Could make the algo engine onion-layered and pluggable. Market of algos for different tastes. For example, one that makes people happy, angry, informed, stupider, kills time, etc.

May also want to pick @mmasnick brain.