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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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Jacque(she|her) 020/100🎥
@jacque
Thank you for having metrics and data. I’ve been speaking about this for months on end if not even years based on how the system is set up to literally push the rest of us downwards versus knowing that we all deserve the same respect as each other.
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