Now that I’m spending most of my reading and almost all of my writing time on a site (Cohost, of course) that doesn’t have an algorithmic-driven recommendation system, I tend to forget how omnipresent they are. I’ve been doing some reading up lately on LLM-generated content and social network amplification, and came across this essay on “Understanding Social Media Recommendation Algorithms.” I think it wimps out a bit in its “can’t live with ’em, can’t live without ’em” conclusion, but overall it’s one of the more useful explanations I’ve seen regarding how recommendation algorithms work—or don’t work as the case may be. (It also has a good discussion of the sheer randomness in what “goes viral”, and how “shadowbanning” and related practices can inhibit virality.)