It has been nearly three weeks since my last analysis of the 
In this study:
- I examine the 2nd and 3rd instalments of the
- I compare the recent movements of capital to those of the 1st instalment analysed in my previous study on 22 January 2018; and
- I then draw interpretations to determine whether this recent power down is likely to be a positive or a negative event for the Steem blockchain.
0 Summary of Findings
I start by presenting a high level summary of findings for readers who have limited available time. The full details of the analysis are included in the later sections of this article.
0.1 2nd and 3rd Power Down Installments
This first diagram charts the flow of money from the
- All amounts shown are in thousands of Steem (so 3000k is 3 million Steem).
- Internal transfers are yellow, power-ups green, delegations blue and transfers to exchanges purple.
The
The
We can see four main flows from the
6.0m of the 11.0m was powered up into Steem Power for the 
2m of the 11m was powered up into Steem Power for the account 
600k of the 11m was passed to account 
Out of 3m originally transferred to the
(It should be noted that the above analysis only shows the direction and amounts of flows on money. Since the
0.2 1st Power Down Installment
This second diagram charts the flow of money from the
The overall pattern of capital flows is very similar:
- Delegation to platform operators and blockchain cleaners through
- Powering up to the
- Transfer out to exchanges through
0.3 Conclusions
Delegations: 60% of power down funds
The delegations made as part of the first instalment release, from
Delegating Steem Power to these alternative blockchain applications also results in significant payouts to the content creators operating on the platforms. In addition to attracting new users, this should also result in Steem Power being spread down to users at lower power levels and in particular to those users producing quality content.
The delegations to
New users: 15% of power down funds
The use of funds to support the
Transfers to exchanges: 10% of power down funds
As noted in my previous study, the use to which these funds will be put is unclear. Without greater knowledge of the use of these funds any conclusion drawn here is in the realm of speculation.
Overall the pattern of use for the second and third power down instalments is similar to that of the first. It would (still) be interesting to understand how the other power down releases are to be used if the power down is to continue since I am still of the view that the above approach does not scale.
Outline
- 0 Summary of Findings and Conclusions (see above)
- 0.1 2nd and 3rd Power Down Installments
- 0.2 1st Power Down Installment
- 0.3 Conclusions
- 1 Scope of Analysis
- 2 Tools Used
- 3 Scripts
1 Scope of Analysis
The analysis is based on the data for the 
Data on transfers and power ups was taken from the TxTransfers table. Data on delegations was obtained from the TxDelegateVestingShares table.
The data has been separated from the overall Steem blockchain data by use of an iterative process through which each recipient of funds was added to a list of accounts to be queried. This process continued until the terminal point for each flow was reached.
The first part of the analysis includes data on transfers, power ups and delegations from 22 January 2018 to 9 February 2018. The second is from 9 January to 21 January 2018. The data has been filtered by date using the timestamps in the respective tables.
2 Tools Used
Valentina Studio, a free data management tool, was used to run the SQL queries. The raw data was then verified and analysed in the spreadsheet application of the LibreOffice office suite.
Graphs and charts were produced using RAWGraphs, an open source data visualisation framework, with colours added in GIMP.
SQL scripts are included at the end of this analysis.
3 Scripts
This was the script used to extract the transfers and power ups for the first two parts of the analysis.
The list of account names was determined by use of an iterative process through which each recipient of funds was added to a list of accounts to be queried. This process continued until the terminal point for each flow was reached. Not all of the accounts in the iterative list make it into the final summary.
SELECT
TxTransfers.id,
TxTransfers.type,
TxTransfers.[FROM],
TxTransfers.[TO],
max(Convert(decimal(20,3), TxTransfers.amount)) as [Amount],
TxTransfers.amount_symbol,
TxTransfers.memo,
TxTransfers.timestamp,
max(Convert(date, TxTransfers.timestamp)) as [Date],
max(Convert(date, TxTransfers.timestamp)) as [Time]
FROM
TxTransfers (NOLOCK)
WHERE
TxTransfers.[FROM] IN
( *iterative list of accounts*
) AND
Convert(date, TxTransfers.timestamp) >= '2017-11-01'
GROUP BY
TxTransfers.id,
TxTransfers.type,
TxTransfers.[FROM],
TxTransfers.[TO],
TxTransfers.amount_symbol,
TxTransfers.memo,
TxTransfers.timestamp
ORDER BY
TxTransfers.timestamp
A similar but simpler simpler script was used to obtain the delegations. The query used the same WHERE clause as the query above and referenced the TxDelegateVestingShares table rather than the TxTransfers table. No grouping or ordering was necessary in this second query.
That's all for today. Thanks for reading!
Posted on Utopian.io - Rewarding Open Source Contributors