social

Farcaster

The good news is that doing social media algorithms is *hard*, so no one really should be faulting Merkle.

I'm sure you've seen the complaints on X (so much so they released their algorithm, never updated it, and now claim to be Grok LLM powered). You've seen the complaints here on Farcaster. 

There are complaints on Threads too!

We once had only "following", which I guess many did get used to (the Facebook timeline/news feed). We were told algorithms would be better for us, but even facebook hasn't solved this since 2006!

Maybe the only people that cracked algorithmic discovery so far has been TikTok. And no, we haven't seen an update to Monolith since they talked about it. https://github.com/bytedance/monolith

hypothesis: text/image feed algos are "bad" because of a lack of preference revealing signals the algos have to determine what you like. the only reliable signals you can get from these feeds are explicit engagement (reactions/clicks/shares)

watch time is a very strong "interestingness" signal

we can’t do read time for text based as a signal?

dev + founder | @vibesengineering.eth @herocast

- biases long casts
- it takes less than a second to read most casts
- you can fit many casts on the screen so how do you know which is being read

we have another "problem" in the sense that this is not protocol level - you can't see "view counts" for example, in the protocol - they are a farcaster client only feature. so if you use herocast this doesn't quite get logged anywhere!

it works better for full screen videos but it can be a great signal compared to just cast interactions 

we have character limit and video length limit. I def need longer to read because I’m slow, can be noisy attention signal for many casts on screen, model will still learn just take more data vs full screen content