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Varun Srinivasan
@v
Been looking at this for techniques to predict "break out" casts https://ai.meta.com/research/publications/detecting-large-reshare-cascades-in-social-networks/
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Dan Romero
@dwr.eth
ok banger algo
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xh3b4sd ↑
@xh3b4sd.eth
When you guys focus on surfacing what most people like, then you are A) doing the same as Twitter (why even bother to do the same?) B) promoting the most average emotional reaction (how is this useful?) There is magic on Farcaster. It is not a magical experience for me to see shitposts about shitcoins only because some click farms in some third world country generate attention. The magic that I value as a real user is to create a connection with an individual, which happened to me more on Farcaster than on Twitter. For me it is possible to meet somebody with the same interest and objective here on Farcaster, and that interest is often rather niche and thoughtful. I think you should lean into that notion more. I don't know how you measure success, but it shouldn't be recasts. It should be human connections made. You are probably more likely to find signal in sentiment analysis of DCs than whatever feed amplification is happening on the public timeline. Because this is all noise.
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Dan Romero
@dwr.eth
> only because some click farms in some third world country generate attention Algo is more sophisticated than that. Not all engagement is ranked equally. Think PageRank
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