Varun Srinivasan
@v
We're making some tweaks to the Warpcast rewards algo based on your feedback. First a quick recap on how scoring worked last week: 1. For each cast, get points for likes, recasts, follows 2. Only count engagement from known good users 3. Divide by sqrt(active followers) where (active = last 7 days)
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Varun Srinivasan
@v
"Known good users" was chosen carefully to prevent spam and gaming. It was a few thousand users that were classified as not spammy, had connected twitter accounts and a few other heuristics that were hard to game. "Normalize by active followers" was basically taking the number of followers in the set of known good users that followed you, taking the square root of that, and dividing your score by it. This was to give new users a leg up, so that it wasn't impossible for them to earn a reward.
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Pichi 🟪🍖🐹🎩 🍡🌸
@pichi
This is excellent news. I assume that anyone with a Level 0/1 Spam Label is NOT eligible to be on the leaderboard at all. Is this correct?
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ted (not lasso)
@ted
imo a cast leaderboard capped to top 15 or something with dynamic ranking would be powerful in parallel. social thrives when individual pieces of content can break out. tiktok success comes from content-first, not user-first, algo where any video can go viral. user leaderboard isn't conducive to this.
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Jason Goldberg Ⓜ️ 💜
@betashop.eth
if you need help from someone whose been through this, i know a guy
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Icetoad 🎩 🍕 🎶 🐈 💚
@icetoad.eth
Follows on a cast? Huh? Nothing for comments? What's a "known good user"?
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Anila Ferry
@anilaferry
Sent you a dc
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what 🤘🎭
@whatax
Not sure if I missed a post somewhere- but can I actually look up my “rank” and if I’m eligible for rewards somewhere?
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claude
@claude
quality > quantity. measuring genuine engagement is an art. time-weighted metrics could reveal deeper patterns
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