A key philosophy in modern platform design: content quality should matter more than follower count. The idea is straightforward—if a new user publishes something genuinely excellent, the algorithm shouldn't gatekeep it behind a popularity requirement. Instead, exceptional content should reach a broad audience regardless of the creator's existing following.
This approach challenges traditional social hierarchy where established accounts get algorithmic preference. By prioritizing intrinsic content quality over network effects, platforms can democratize visibility and give merit-based discovery a real shot. It's an interesting angle on how algorithms can be structured to surface talent and ideas rather than just amplify existing influence.
Whether this works in practice depends heavily on how "excellence" gets defined and measured—but the principle itself aligns with how decentralized networks often approach content meritocracy.
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AirdropHunterXiao
· 01-11 01:59
Well said, but it feels like all talk and no action. How many platforms can truly achieve it...
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AirdropATM
· 01-11 01:56
NGL, this is too idealistic. It sounds good, but in the real world, it's not that simple...
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MEVvictim
· 01-11 01:54
Decentralized algorithms sound good, but I'm worried that in the end, it's still the big influencers who have the final say.
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AirdropHunter420
· 01-11 01:54
NGL, this ideal is too perfect; the reality is that the number of fans is still the best and most reliable metric.
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MaticHoleFiller
· 01-11 01:43
It sounds ideal, but to be honest, who defines what truly constitutes "high-quality content"? Isn't that still subjective?
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ZKSherlock
· 01-11 01:32
actually... defining "excellence" in algorithmic terms is the hard part nobody wants to talk about. like, are we using some probabilistic proof system to verify content quality? bc whatever metric you choose becomes a new trust assumption that could totally be gamed. seen this movie before tbh
A key philosophy in modern platform design: content quality should matter more than follower count. The idea is straightforward—if a new user publishes something genuinely excellent, the algorithm shouldn't gatekeep it behind a popularity requirement. Instead, exceptional content should reach a broad audience regardless of the creator's existing following.
This approach challenges traditional social hierarchy where established accounts get algorithmic preference. By prioritizing intrinsic content quality over network effects, platforms can democratize visibility and give merit-based discovery a real shot. It's an interesting angle on how algorithms can be structured to surface talent and ideas rather than just amplify existing influence.
Whether this works in practice depends heavily on how "excellence" gets defined and measured—but the principle itself aligns with how decentralized networks often approach content meritocracy.