Farcaster

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.

The rewards algo needs a complete rethink 

People have figured out that posting a lot of low effort content (especially videos) is the way to get to the top

And it’s clearly too biased towards new users, makes it really easy to game 

People see these strategies working and copy them, basically incentivizes slop

building @emptyblock / prev director of research @coinmetrics

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https://portrait.so/pichi

Not going to call people out, that’s not the goal here. But if you check out the top 5-10 I think it’s pretty apparent 

Glad to hear the new algo is rolling out. I know it’s hard to get right but I appreciate the fact that you guys continue to iterate

the new algo is rolling out, but actually, last weeks rewards with the old algorithm did quite well. i looked through it the final results and didn't see any obvious slop.

@nmadd can you please link to accounts that you think are posting slop and placing in the top 100?