Starting with the lightest weight version possible, I’d like to understand “How people think about recommendations”, “Why they think that way”, and “What algo gets them something in the ballpark of that thing”
Ok then start with that: https://towardsdatascience.com/recommendation-systems-explained-a42fc60591ed Also understand PageRank. Then, the relationship between users and likes in movie recommendation systems. There are some trainings sets of IMDB somewhere with examples. Then look into neural nets recommender sys.
This book may be too basic now, but back in the day I found it useful. https://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325 More generally, it sounds like you want to study some behavioral economics. I have tons of recommendations there.
I'm building a Farcaster client, and I've been thinking about this a lot. Currently, the most interesting feed I can come up with is some specific search terms (btc, eth, nouns) and a list of people. Nothing algorithmic yet.