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mvr 🐹
@mvr
So I've asked ChatGPT to analyse the data from the Rewards Leaderboard Top 10 I shared yesterday (thanks for the tip @dosir). This is what it came up with Should we do this again next week? 📊 Key Insights - High concentration of influence and interaction among top leaderboard creators and their superfans — with some appearing as top fans for 5+ creators. - A potentially self-reinforcing system — those at the top engage with one another and remain highly visible. - New reward logic could reduce “circular value exchange” — ideally diversifying who earns and who gets seen. - Some users (like monadver, ejire5, gfam) may be acting like “engagement miners”, systematically liking/commenting on top creators. ✅ Suggestions (If You're Evaluating the System) - Introduce diminishing returns on repeated engagement from the same user to the same creator. - Reward diversity of fans — e.g. reward creators who attract engagement from new or varied FIDs. - Visibility of top fans could itself become a reward metric, encouraging healthy discovery vs mutual reinforcement.
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乃ㄥ卂乙乇ᗪiҜ乇几
@degencummunist.eth
Yo where are you searching for all this data? Dune? Neynar? Like what if I wanted to see my lifetime tips where should I go?
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mvr 🐹
@mvr
I've fetched them from snapchain directly, combined it with some other json sets I have
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乃ㄥ卂乙乇ᗪiҜ乇几
@degencummunist.eth
😲ohhh! Ye I can’t do all that😅🥲
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Quazia
@quazia
It's easier than you'd think, we offer snapchain instances you can pull data from - you don't need to self host a node 😁
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mvr 🐹
@mvr
But also that's quite easy to accomplish Can also try read from free nodes like pinata
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Quazia
@quazia
Pinata hosts a free snapchain read node? That's cool!
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