A few weeks ago, I calculated the Gini coefficient for Steemit and wrote an article about it after stumbling over the Steemit Whales Service where all users are listed in detail incluing the overall account value.
Steemit as a country...
My verdict back then was not very flattering, because it turned out that Steemit had a Gini coefficient of 76.3 which puts it into the global top five - or more the bottom five - if it was its own country. What made matters worse is the fact that I only considered the 1,000 most valuable accounts. But even without the top 100 accounts, the coefficient for the ranks 101 to 1,100 was still 45.1, which one user commentated with "So, better than Panama now. Woo hoo!"
The wealth distribution on Steemit is very tilted to say the least, but I have hopes that the situation improves. Because after all, there is actually some movement going within the ranks. To check up on that, I decided to calculate the Gini coefficient again with the numbers of today.
The Gini Coefficient Of The Top 1,000 And The Ranks 101 to 1,100
According to my numbers which you can find here and here in the form of a spreadsheet, the situation seems to have gotten worse - if you see a wealth concentration at the very top as concerning..
The top 1,000 have now a Gini coefficient of 76.84% (before 76.33%):
The ranks 101 to 1,100 have now a Gini coefficient of 45.73% (before 45.1%):
This is not good. I have expected a distribution that is slightly more even than three weeks ago. Instead the opposite. Both numbers worsened by about 0.5% which is significant, especially when considering the short period between the numbers). The close numbers also indicate that my calculation is correct (or that I got it wrong both times the same way..).
Please feel free to do your own calculation. Considering this change into the "wrong" direction it is better, when there is a second independent number showing the same development.
Possible Weaknesses And Aspects To Consider
Besides the fact that a growing Gini coefficient must not necessarily be a negative development, there are also other things to consider when discussing the results:
- As mentioned above, the numbers or the calculation could be wrong.
- I only considered the top 1,100 of all accounts and I do not know how the situation below is changing.
- External effects aren't considered (like buying more Steem Dollar or the time actively spent on Steemit).
- Maybe the whales are just more active and virulent than everyone else.
Overall, I don't think these aspects would change too much - at least not to the better.
What Needs To Be Done?
First of all, I think the number base must become better. In the next days, I will use the daily statistics by 
Another interesting thing would be to get more Gini coefficients. Unfortunately, the Steem Whale site only allows the display of 25 users at once and it takes a while for the data to be displayed. With the necessary access to the Steem database, it would be particularly interesting to see how users develop relative to their activity and size.
I still believe that this would show a more positive development.
But in case this first impression of a wealth concentration hardens, Steemit has a real problem. 
If a concentration is happening and despite smaller users trying their best to break through the glass sealing to become a whale, then there needs to be some mechanism implemented on the platform to turn around (or at least stop) this tilted distribution.