Food For Bots
When it comes to curation rewards, Whales (and Dolphins) are in fierce competition. Ultimately, this boils down to an information game, making the smartest choices you can with your votes, based upon the rules of the game. @dantheman recently posted his thoughts about this issue, where he mentioned that this competition requires Whales to use Bot Algorithms. Further, he described the role of Dolphins and Minnows as being one of generating data for bots to use.
When bots are attempting to identify content to up vote they will take clues from minnows. Good dolphins can even start to earn curation rewards when whale-bots pick up on their usefulness as an early indicator. - Dan
In this way, Minnows and Dolphins who vote accurately, can actually begin to have a large impact indirectly. Some whales will begin to tune their bots to vote on everything that top curating Minnows and Dolphins vote on. In this way, there emerges a greater incentive for Dolphins to vote accurately, since having posts upvoted by Whale's Bots after you upvote can yield modest curation rewards.
Creative Commons: Source
Note: This is probably mainly a game for Dolphins and note necessarily minnows. Because of the relationship between curation rewards and Steem Power, an account must have at least a certain level of Steem Power to achieve curation rewards, regardless of how much skill you have when voting.
Quantifying Curation Skill/Ability
The question then becomes: how can we quantify Dolphin's and Minnow's curation "ability"? Here I present a simple technique for quickly estimating someone's skill at identifying valuable content. My hope is that this information will prove valuable to bot designers. After all, as Dan said, an "evil-whale" is one who makes easy profits due to lack of competition. Since this is ultimately an information game, I want to present these results to the whole community, with the hope that publishing up to date, relevant information will increase competition, and decrease the odds of emergent "evil-whale" behaviors.
It is not appropriate to simply compare an accounts total curation rewards over a fixed period of time. This is because curation rewards scale with N Log(N), where N is an account's Steem Power. A single random vote from a whale could easily yield more curation rewards than 100 perfectly-timed, intelligently-placed minnow votes. For this reason, we must normalize each user's curation rewards (over a certain period) by the value of N Log(N) for that account. This normalized value then gives a simple numerical "score" to describe users' curation abilities.
Show Me The Data!
Since I like chunking through data, I have determined a curation "score" for each of the top 500 accounts on steemwhales.com. The reason I limited it to this range (Whales and Dolphins), is partly because acquiring the data was taking a decent amount of time, but mainly because I assumed that only these larger accounts would have a sufficient interest to put forth the effort to play the game and try to maximize curation rewards. Still, I do not discount the possibility of smaller accounts having greater curation "scores". If this type of data proves valuable to the community, I will attempt a more thorough characterization of all accounts. Still, it is likely that the top curators I have identified would still be top curators if more minnows were included.
The following figure shows the data, ordered by curation "score". The first column shows the user's whale rank according to steemwhales.com, the second column gives the username, the third column gives the account's Steem Power as of a couple hours ago, the fourth column gives the account's total curation rewards for the past week, and the final column gives the normalized curation score. This was calculated by taking the curation rewards divided by N Log(N), where N is the account's Steem Power, and finally normalizing by the maximum score, to give a max score of 1.
What Can We Learn From This?
- NO super whales are super curators. Out of the top 30 curators, the highest-ranked whale to appear is @wang, who ranks 27th on the Whale scale.
- The majority of high-performing curators are modestly-sized dolphins. The median Steem Power of the top 30 curators is about 27,000, which is probably not in Whale-territory quite yet. These slightly larger dolphins have an incentive to play the game and try to gain curation rewards, and we see that in the rankings.
- @recursive2 is ahead of the competition. This account is probably owned by @recursive, who is in whale territory with 192,000 Steem Power and possibly has a clever Bot working for them to capitalize on curation rewards. Well done!
- Keep in mind that a week is still a fairly short time period. I have seen my weekly curation rewards range by up to 100% or more as I try to find valuable content. These rankings are probably good estimates of curation ability, but they are obviously subject to fluctuations and random chance.
Bots Need Humans
One very important takeaway from these results, is that humans can outperform bots. I was very happy when I discovered that I am the 6th highest-ranked curator (based upon this simple metric). However, I was even more surprised to see that I had beaten out @wang, by more than 60%. This means that if @wang switched to a far simpler voting algorithm that simply immediately votes on everything that I vote on, he could increase his curation rewards by almost 60%! This is what it means to provide valuable information. Dolphins and Minnows can provide this type of information to Bots and their operators, providing a valuable service, for which they can be rewarded (by having the content that they upvote be immediately upvoted by Whale's bots).