I have viewed my feed in gossip (gossip lets you view a relay's global feed) and it was tailored to me.

One note seemed strangely irrelevant (not very connected to me nor reacted to much).

It appeared to me that as I went down the feed, there were fewer events per time period, and those had to be much more popular (based on reactions).  Which makes sense.

I'd love an English description of the algorithm. 

 It doesn't respect since/until filters, only limit. Works best if you just do a big limit to start.

It blends mostly personalized notes and mixes in viral posts as well.

I've done my best to write up how the algorithm works on GitHub, let me know if you think it needs some more meat.

Definitely will be improving it overtime, stay tuned! 

 Ah, well gossip is using since/until as well as limit in order to load chunks at a time with a known number of events.  It also specifies kinds (that the user has selected and that gossip knows how to display).  But it still worked pretty well.  I'll read the github notes shortly.