Recently active Hive authors and their rewards

Yeah, you have been at hive for a long time, and seen many plots on hive related data, but I bet you have never seen a plot like this! It is amazing how much you can do with data these days, and how much the data tells you about behavior of crowd.

Thanks to @beaker007, I have been looking at a lot of hive and splinterlands user data lately. Lot of the visualization of the data I have been able to do only because of him and some of the other prominant hivers like @slobberchops.

The trouble of any data query at hive, is the fact that the moment you want to go deep into the lower HP domain, you almost hit a wall. This is because there are too many inactive accounts that were created over the years and are now defunct. In order to do any kind of data analysis, such accounts just slows everything down. I also know how to identify those accounts in terms of my simple indentifier: Investors or Extractors. I will just classify those 'dead' accounts as extractors and move on. However, the reverse question is more important. How do you identify an active account? There are many way to answer that and I am not going to get into that debate too much. Let me tell you how I identified these 4349 accounts (which are active) that is plotted above. I was looking for active authors or at least commenters. Here was my criteria:

• Accounts with author rewards > 500 HP
• Accounts with comments > 10
• Accounts which made those comments/or posts in last 6 months

In order to get author reward, they must create a post. To get 500 HP author rewards, the account must make many posts, just commenting and getting upvotes in comments will not get you 500 HP author rewards easily. The 10 comment cut-off is a low number, but lot of the farmers don't comments much, and I did want to include them. The 6 month cut-off is arbitraty, but I am not interested in people who left a long time ago. We have pondered on them enough, and it is time to move on.

So that was my logic for the selection. I must make sure, that I explain, that whether that number is 4349 or 8000, or 12,000 matters not to me. I just wanted to have a large enough sample to play with so that people can't talk about sampling biases.

Source

The Plot

I already wrote a wall of text, and the plot is too far above:) Let me put the plot back down here again.

This is a plot of 4349 'active' hive accounts. They are ploted according to their HP rank along the horizontal axis, from the highest to the left (rank 1) to lowest to the right (rank 4349). The vertical axis is HP ploted in log-scale, so that I can plot 1 and 1 million at the same time. The data clouds are:

• Blue = Total Rewards (Author + Curatiom)
• Orange = KE Ratio (Author rewards + Curation rewards)/Held HP
• Red = Held HP
• Magenta and Green dash lines are manually drawn bands, ignoring the outliers
• Yellow dash straight line = 500 HP cut-off that I used to get the data

Observations from the Plot above

Overall, KE Ratio increases with lowering of held HP. This is no surprise as held HP is in the denominator. However, the change is dramatic as soon as held HP drops below 200 HP.

• below 200 HP; average KE = 11,010 (there are 717 account that falls on this spectrum)
• above 200 HP; average KE = 5.5 (there are 3631 account that falls on this spectrum)

Well that 11K average is skewed because of a few accounts with less than 1 HP :). Let me take them out. These are those 20 'authors' by the way.

If I ignore them, for accounts that hold below 200 HP, the average KE = 169.89!

Did you get it? This is a massive dataset. When people holds more than 200 HP, their 'behavior' in terms of hive etiquette is about 30X better than those that holds less! We have excluded, worst of the worst from this calculation.

Here is the disclaimer: Since KE is a ratio, its effect is really prominent when the held HP gets very low, as it is in the denominator. But that said there is a trend of the exploitation among low HP accounts that can't be ignored.

Governing Dynamics 2.0

When I first published the data of top 2500 hive accounts back in August 2024, I included every account. It was described in this post. That first plot in that post is below:

The problem with this previous plot is it included all accounts regardless of if they post on hive or lot. A lot of them were inactive, some were investor account, some were curation only etc. So the plot was very noisy. This time around I am focusing on recently active accounts (6 month prior, we can use a different time frame if we want), who had written posts, created content on hive blockchain, and were rewarded as authors.

The immediate difference you might see, is there is no account below 57 (which is the lowest on this very large sample). Most of the accounts are above 60, and show a nice trend, and large clustering. 50 - 100 K HP and 65 - 80 reputation. Reputation here is a function of upvotes received or author rewards. The outliers of these plots are far and few and highly visible.

• People who got a lot of rewards and sold it all: kingscrown, anomadsoul high on the Y-axis, low on the X-axis

• People who don't post much, but likely bought HP, bubke with 92K HP and 0.12, low of the Y-axis, high on the X-axis

• People who post a lot, and still held decent HP, like oflyghigh, taskmaster4450, high on both X- and Y-axis

These people are all outliers. I have tried to label as many outlier as I can. We can look at each group of people in detail at a later post. This post is already way too long.

However, if I don't mention one thing from the first plot then I probably won't be able to sleep at night!

• lets say you hold 5000 HP, among your peers who hold similar HP, you could have gotten 5000 HP rewards or 35,000 HP rewards
  • a factor of 7X difference!
• lets say you hold 4000 HP, among your peers who hold similar HP, you could have gotten 1800 HP rewards or 28,000 HP rewards
  • a factor of 15X difference!
• towards the right side, the range is fairly constant, for the same HP, you could earn 500 HP or 22,000 HP rewards
  • a factor of 44X difference!

Please, I want you to think about this. What is some of your peers are doing? Which vote trail or curation program some of your peers are on? How come they are getting 40X more rewards compared to you?

Let me rephrase that!

Some of your peers are getting 10 to 80 times more rewards than you!

What are you not doing?

We are going to look into this more accurately on a log-log plot. Here is the Table for that. It will give you a lot to think about. Also there is the chart below that leads to the table for your consideration.

Peer Group HP	Low End HP	High End HP	Factor
1000	600	50,000	83X
3000	1500	70,000	46X
10,000	4600	120,000	26X
30,000	12,000	300,000	25X
100,000	35,000	400,000	11X

By the way, this is obvious, but still I should mention it. Since for each 'peer group' the HP is similar, and their total rewards vary dramatically, their KE will also vary proportionally.
As KE = Total Rewards/HP.

Why do you think the total rewards are so much different between the peer groups? Many reasons:

• Age of the account, more time, more rewards
  • if they hold same HP today and if ones total rewards is 10X higher, then KE should be proportionally higher
• More engagement, the higher rewarded user must have more connection with the community
• Favorable curation, the higher rewaded user must get regular upvotes from large curation programs
• Consistent posting, the higher rewarded user like a consistent poster, if not now, must be in the past

There could be other reasons that I might be missing, do let me know and we can investigate. It is all in the data.

KE Ratio Variability within Peer Groups

Similarly we can plot the KE Ratio variability. The results are similar:

Peer Group HP	Low End HP	High End HP	Factor
100	5	500	100X
300	1.9	105	55X
1000	0.6	81	135X
3000	0.2	17	85X
10,000	0.15	14	93X
30,000	0.12	5	41X
100,000	0.1	2	20X
300,000	0.1	1.5	15X

Hope this helps the curators if they like to use this information.