Steem economics analysis: beneficiary payouts distribution

in #utopian-io5 years ago

Hi Steemians! Recently I conducted an analysis of beneficiary payouts distribution over Steem account and today a want to show you my results. I hope it will provide you with a clear vision about how many apps use this feature, how many tokens they receive with it and which apps are at the top of payments. To answer this questions I collected data about all posts between 2018-01-01 and 2018-10-31.

Results

There are 9,671,014 posts made between Jan 1 and Oct 31. The most of them (6,936,438 or 71.7%) didn't have beneficiaries and less than one-third of them (2,734,576 or 28.3%) had at least one beneficiary:

Posts with/without beneficiaries ratio

Interesting that if we look at total payout value distribution we will see that posts with beneficiaries received an even smaller proportion: only 15.4% (3,728,646 SBD).

Posts with/without beneficiaries payout sum

That means that posts without beneficiaries received more valuable upvotes than posts that gave a percentage of their income to apps. And indeed, if we look into a mean total payout value in these two groups we will see that in the group of posts without beneficiaries it is equal to 2.959 SBD whereas in the second group this value is equal to 1.364. A similar pattern is observed at the distribution of a max payout value: in the first group this value is equal to 1967.32, while in the second group it is equal to 982.11

Beneficiary percent

If we look at the following plot we will see that most of the posts have a beneficiary percent less than 25:

Beneficiary percent distribution

Beneficiary payouts sum

Now its time to answer the main question: how many tokens app earned by beneficiary payouts and how these payouts were distributed between apps.

There are 1591 accounts that were set as beneficiaries at least once in the reviewed period. The total sum of all beneficiary payouts in the reviewed period is 401,249 SBD. If we look at the subset of beneficiaries who receive a sum of payouts more than 10 SBD, we will see that the 75% of such accounts receive less than 283 SBD.

Top beneficiaries

As we can see from the above plot there is a big gap in payout sum between several top apps and other beneficiaries. In fact, the top 5 apps received 87.5% percents of the total sum:

Another interesting finding is that the five of ten top apps are very specific in terms of content: Dtube, Dsound, Steepshot, Zappl and Zmania.

Also it should be noted that the amount of beneficiary payout decreased over time:

I prefer that this can be related to the situation on the crypto markets, and, therefore, to the interest to blockchain and cryptocurrencies. But this interconnection should be analyzed separately, as well as correlation with other factors, such as the total payout value sum at the concrete date and the number of posts.

Conclusion

This analysis shows several important trends in beneficiary payouts distribution.

  1. At first, it shows that only less than one-third of posts pay beneficiary payouts
  2. Posts that pay beneficiary payouts have a smaller total payout value than other
  3. Most of the apps set beneficiary percent less than 25%
  4. Most of the beneficiaries don't receive really big money, and only a small subset of apps receives the most of payouts.
  5. At least half of such apps are very content specific and offers unique features that are not available on other platforms

Summarizing the above it can be assumed, that the best way to receive a lot of beneficiary payouts is to build a service that will offer some specific features to interact with content. But, on the other hand, such content at general receives smaller payouts than entries posted with regular clients.

Tools and Scripts

All scripts used in the analysis can be found in this Jupyter notebook
Data for this analysis were retrieved from SteemSQL database.

Relevant Links and Resources

There are some links describing beneficiary payouts feature:

Repository

steem-sigma/papers

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Hi @ninjas, great to see a new contributor in the Utopian analysis category - welcome and great start! I see this is your first utopian contribution - awesome!
An analysis with a similar scope was published by @paulag around two months ago here. Your results on the distribution of the beneficiary account seems mostly in line with Paula's results. However, I think there are a few issues with your approach that might have led to not fully correct results:

  • with_benef.beneficiaries.apply(lambda d: d[0]['account']) -> I think this captures only the first beneficiary of each post, while a post can have up to 8 beneficiaries. There are a couple of Steem apps that set multiple beneficiaries.

  • that part is unfortunately not correct:

with_benef['author_payout_value'] = with_benef.total_payout_value - with_benef.curator_payout_value
with_benef.author_payout_value = with_benef.author_payout_value.astype('float64')
with_benef['benef_payout_value'] = with_benef.benef_weight * with_benef.author_payout_value / 100

Despite its name,total_payout_value is only the author share of the post payout and has possible beneficiary rewards already removed. As a result, subtracting the curation rewards from this author share and then additionally reducing this by the beneficiary weight gives lower rewards than what the beneficiaries actually received. The comparison of the payouts of posts with and without beneficiaries as well as the sums of benefactor rewards are affected by this.

Summing up rewards over time in general has to be treated carefully, depending on what you want to show. Since the Steem price lost a factor of ten since the start of the year, the SBD payouts are also affected from this. A metric that is independent of the price could be to look at the sum of vote rshares per post, but that easily goes deep down the rabbit hole...

Nevertheless, great start, and we'd love to see more from you! Feel free to contact us on discord (see link below) if you have any questions.

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Thank you for your review, @crokkon! Keep up the good work!

Hi @ninjas!

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