The interest graph is built in response to your content upvotes/downvotes. The connections are float values instead of booleans. Here is how these float values are updated:
1. You start off weakly connected to all users and you see generally popular content.
2. When you upvote something - you get stronger connected to other users that upvoted that content before you (you don't connect to those who upvoted after you - this is a proof of work that Eugene wrote in https://www.eugenewei.com/blog/2019/2/19/status-as-a-service). The stronger your are connected to someone => the more weight their other upvoted items have for you => the higher their other upvoted items show up in your feed.
3. When you downvote - your connection to those who upvoted that content goes weaker. And your connection to those who also downvoted it goes higher.
4. Every time someone you are connected to upvotes something, your connection becomes slightly weaker to them. They sort of place a bet that this item is worth your attention and that bet is lost if you ignore that item. So if you ignore those who no longer post useful content or simply post too frequently for you - they will gradually disappear from your list. This prevents the old money problem from the same "Status as a Service" post above.
5. You can put the items you upvote into user-defined collections, so your tech content could go into your "tech" collection and users that are connected to your tech collection will not be bothered by the stuff you put into your "film" collection. This is similar to different boards on Pinterest.
This system is somewhere between popularity based systems (Reddit), subscription based systems (RSS, Twitter) and algorithmic systems (TikTok, Pinterest).
Your connections to other people capture how useful their previous recommendations have been to you (ie, their signal-to-noise ratio) and so can be thought of: how much you can trust them that their future recommendations will be worth your time.