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RE: Why Steem curation reward is needlessly unfair and how to fix it

in #steem • 8 years ago

Above example is voting after a whale. Here is another example of voting after crowd:

  • assume that a post which already got some up-votes have total_weight = 10 and rshares = 20 and reward = 400, then a new voter up-vote with 1 rshare, so her
  • weight = 1 * 0.5 * 10 / 20 = 0.25, so
  • new_total_weight = 10.25, and
  • new_total_rshares = 21, and
  • new_total_reward = 21*21 = 441, so the new voter will get
  • reward = 441*0.25/10.25/2 ~= 5.4, which is even higher than above example.
8 years ago in #steem by
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     8 years ago 

    Above examples are based on using rshares * rshares as weight for reward distribution among posts. That said, if post A has 2x of rshares in comparison to post B, then total reward to post A is 4x of reward to post B.

    While one's weight% to a post is near linear to current rshares of the post if she votes late, the reward she can get is also near linear to current rshares of the post. That said, by adding a vote to post A the voter will get around 2x reward in return in comparison to voting on post B.

    This is the reason why the algorithm described in OP encourages voting on already popular posts. If we want to encourage people to find new quality post, it's likely we need to make the weight for reward distribution among posts linear to current rshares or less.

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