This is an analysis of the voting habits of ,
, and
over the last 3 months.
The aim of this analysis is to compare the voting 'styles' of the above accounts to find out more information with regards to:
- Voted Steem account reputation - 7/30/90 days
- Unique author coverage
- Popular author vote counts
Each of the above will be analysed over a 7, 30, and 90 period, with an overall analysis summary to conclude.
Contents
- Introduction
- Votes by Steem account reputation
- Unique author votes
- Vote counts - popular authors
- Summary analysis
- Tools and queries used to gather data and compile this report
1. Introduction
The 3 accounts analysed in this report are ,
,
. I have chosen to compare these accounts to try and guage:
- If there is a best account/application to aim your time at, depending on your reputation
- If these accounts are supporting many users by spreading their vote / loyal to their contributors
- If it is possible to frequently be supported by any of these accounts
is the open source project for open source projects, housed on the Steem Blockchain.
joined the Steem Blockchain in September 2017 and holds over 3.6 million Steem power through delegations from its kind sponsors.
Curie is a meritocratic, voluntary organization which supports the development and growth of new and existing authors on the Steem blockchain. source
joined in September 2016 and has 115,000 Steem Power. However,
has a long voting trail that include one of the largest 'user' accounts on the Steem Blockchain.
is a decentralised video sharing platform and is built on the Steem Blockchain. Clear comparisions can be made with YouTube, both in name and content.
currently holds just over 1 million Steem Power through delegations.
Each of these accounts (and trails) can provide a sizable vote to content deemed worthy by their curation teams/moderators. Which accounts do they vote for? How many votes do they give out? Do we have to be a popular author to get a vote? Perhaps the numbers can provide the answers.
2. Votes by Steem account reputation
7 day data
The following chart show the votes cast by each account over the previous 7 days.
has cast a total of 2212 votes over accounts which average at a reputation of 52.97.
has cast a total of 558 votes over accounts which average at a reputation of 53.31.
has cast a total of 981 votes over accounts which average at a reputation of 52.93.
Whilst has cast the most votes, it is
that has voted for the lowest average reputation.
has cast 41 votes for a reputation of 70 or above, whilst
and
have voted only once each for an account with 70+ reputation.
30 day data
The following chart show the votes cast by each account over the previous 30 days.
Summary
The data above has been compiled to include the 90 day voting totals and reputation average and listed in the following table.
Across each of the time frames analysed, casts the most votes but it is
that supports the lowest average reputation.
Over the past 90 days, has cast over 150 votes to accounts with a reputation of 70 or higher.
From this data, we could suggest that for accounts with a lower reputation have a greater chance of success by posting blog content on Steemit (busy.org and others), and utopian-io. And accounts with a higher reputation could be more likely to succeed by posting video content on dtube.
3. Unique author votes
By looking at the number of votes for unique authors, it is possible to gauge which account is supporting the widest set of users.
From the table above, we can see that over the 7 day period it is that casts votes to the widest set of different accounts. However, when we look at the 30 and 90 days totals, it is
that has reached the widest set of unique authors.
It is worth stating here that data should be taken with caution as has the breadth of the Steem Blockchain accounts to target, where as
and
are almost exclusively only voting on content posted to their applications.
It is likely the case that there is a smaller subset of authors posting to and
and so the number of unique authors voted for is lower than
.
If we compare against
, we can see that there are about 300 more unique votes cast by utopian-io in each time frame analysed. It would be interesting to see if this figure changes in future.
4. Vote counts - popular authors
In this section, we look at the vote counts for the top authors by the 3 accounts in this analysis.
7 day top author vote count
In the past 7 days, we can see that votes on average, 7 times for the top authors receiving a vote. This votes are most likely to be 'smaller' votes for budding new authors that have been spotted by the curation team.
Both and
show that it is possible to pick up a vote more than once per day, with the top two
authors receiving an average of over 3 votes each day over the last 7 days.
30 day top author vote count
90 day top author vote count
For both the 30 and 90 days time frames assessed, the trend continues with voting once each day for the top 20 accounts receiving a vote.
The top 2 accounts have received an average of 2 votes a day for the past 90 days, and one account submitting to
has also almost reached an average of 2 votes in each of the past 90 days.
From these figures, we can say that is again spreading the vote to a wider selection of accounts.
As above, it's likely that this figure is due to a wider available audience to vote for.
The data also shows that their is potentially no limit to the number of votes that can be given to a particular author by both and
.
5. Summary analysis
With regards to , it is reasonable to suggest that with the highest average reputation votes, and larger number of votes to accounts with 70 and above reputation, this account has a slight bias to more 'well established' authors. It also seems likely that once you have received that first vote, you could well be followed/voted further.
is the clear leader in the total number of votes issued. We can also see that
will vote for an author as often as they submit approved content. Will only a few votes for reputation above 70,
votes a lot for newer authors.
has the lowest reputation average across all 3 time frames. This shows a clear willingness to support new authors. With over 3000 unique author votes in the past 90 days,
also supports the widest selection of authors - this is complimented by the general average of 1 vote each day for each author in the top 20 vote total for each time frame.
From this analysis, I would suggest that newer authors might be best contributing content via Steemit (busy.org etc.) and . Whilst more established accounts, could perhaps look to
, if they are willing to submit video content.
However, if the content is up to the desired quality, it is very possible for any author to receive a votee from ,
, or
.
A future analysis could be done based on the above, but with the inclusion of more 'community accounts/applications' and with an inclusion of the number of followers that the accounts receiving votes have.
6. Tools used to gather this data and compile report
The data is sourced from SteemSQL - A publicly available SQL database with all the blockchain data held within (Data is normally 1/2 hours delayed from live)
The SQL queries to extra to the data have been produced in both SQL Server Personal Edition and LINQPAD 5.
Code examples:
Popular authors - 7 days
Distinct authors - 7 days
Vote count - 7 days
The charts used to present the data were produced using MS Excel.
This data was compiled on the 2nd February 2018 at 11:00 pm (UCT+4)
I am part of a Steemit Business Intelligence community. We all post under the tag #blockchainbi. If you have analysis you would like to be carried out on utopian-io/Steem data, please do contact me or any of the #blockchainbi team and we will do our best to help you.
Thanks
Posted on Utopian.io - Rewarding Open Source Contributors