Utopian.io - Full Year 2017 Statistics

In this third study of the 2017 full year statistics for the steem blockchain platforms I will look at the figures for Utopian.io.

Utopian.io is a platform built on top of the steem blockchain with the aim of rewarding open source contributors. Contributions to the platform must be related to open source projects but are not restricted to development work or bug-hunting; other categories of contributions include analysis, tutorials, translation, graphics and copywriting. Contributions are rewarded in the same way as other steem blockchain articles, using a stake-weighted voting system to distribute newly minted steem, but additionally benefit from a significant vote from utopian-io if the contribution passes the moderation rules for quality.

The Utopian.io project launched in September 2017 and this analysis over 2017 thus contains four months of data.

There are four parts to the analysis:

• Overview of 2017: An overview of the figures for the full year 2017 (daily individual author numbers, post numbers and reward payouts) illustrating the rapid growth in the platform over the lat three months of the year;

• Analysis by contribution type: A breakdown of the contributions by category type (development, analysis, tutorials etc) to illustrate where contributions and rewards are heaviest.

• Analysis by organisation and repository: A breakdown of the contributions by organisation and repository to illustrate which projects are benefiting from the launch of Utopian.io

• Top 50 users: A summary of the payouts for the top 50 users over 2017 showing those users that have had most financial success through the platform and their main categories of contribution.

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Outline

1. Scope of Analysis
2. Tools Used
3. Overview of 2017
4. Analysis by contribution type
5. Analysis by organisation and repository
6. Top 50 users
7. Scripts

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1 Scope of Analysis

The analysis is based on the data for the Utopian platform obtained through SQL queries of SteemSQL, a publicly available Microsoft SQL database containing all the Steem blockchain data.

The Utopian data has been filtered from the overall steem blockchain data by use of the app label information in the json_metadata column of the Comments table. One limitation of this approach is that modifying an article in another application causes the app label information in the json_metadata column to change to that of the modifying platform. However it is expected that this limitation has minimal effect.

The analysis focuses on articles posted in 2017. The data has been filtered by date using the timestamps in the created column of the Comments table.

Category and repository information has been obtained from the type and repository.full_name label information in the json_metadata column of the Comments table.

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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 Numbers, the Mac spreadsheet tool, or using RAWGraphs, an open source data visualisation framework.

SQL scripts are included at the end of this analysis.

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3 Overview of 2017

The Utopian.io project launched in September 2017 and showed rapid growth over the last three months of the year. In December it had risen to the third largest application on the steem blockchain ranked by total post payout, or sixth ranked by number of users posting articles.

The chart below covers the last three months of 2017 for the Utopian platform:

• The light blue line is the number of articles per day and the dark blue line is number of distinct authors. These are plotted against the left hand axis.
• The silver columns are author rewards and the gold columns are curator rewards. These are plotted against the right hand axis.

^{2017 main metrics - Utopian}

The chart illustrates the attractiveness of the open source proposition to users of the steem blockchain. There has been exponential growth in users, articles and payouts over the last three months (although it is noted that the growth in rewards was assisted by the rise in the steem price over December, from US$1 to US$3).

Finally the table of monthly figures for Utopian summarises the overall results by month.

Month	All Posters	Regular Posters	All Posts	Total Payouts
Sep	1	0	1	227
Oct	199	36	567	7,210
Nov	554	192	2,743	65,031
Dec	1,270	624	9,758	221,268
Total	2,024	852	13,069	293,737

The December figures showed over a 200% increase in regular author, post and reward numbers.

The figures also suggest an overall average payout of around $22 per article.

Looking to 2018 it will be interesting to see whether user numbers and payouts continue to rise, or if there is a plateauing from a saturation effect on the platform, with individual rewards reduced by increasing numbers.

Whilst the steem price has again risen in January, effectively giving the project additional funds for payouts, there has also been a stringent tightening of the quality requirements for Utopian contributions which may deter some users.

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4 Analysis by contribution type

The aims of the second and third parts of the analysis are to understand what kind of work is being carried out and rewarded (part 4) and which projects are benefiting from this work (part 5).

The chart below shows post payouts (orange columns - excluding the utopian beneficiary payments) and post numbers (blue dots)

^{Breakdown by contribution type}

Far and away the largest category, both by popularity of contribution and by payout, was translations. Tutorials ranked second under both metrics. Development was third most rewarded and seventh most popular contribution.

I would expect this pattern to significantly change over 2018. The recent doubling of rewards for development would be expected to significantly increase contributions from this category, whilst the increased stringency over translation and tutorials may well reduce contribution in these categories.

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5 Analysis by organisation and repository

The circle packing diagram below shows the organisations that have most benefitted from the work carried out by the Utopian project. The size of the circles represents the payouts from utopian posts (there is an assumption made that the size of payout is a better proxy for the benefit to the project than the number of contributions - no measure will be perfect here).

The organisations and repositories have been extracted from the json_metadata and should reflect the file structure on GitHub. Some organisations may not be well known and as such I have added the most popular repository for clarity. Unfortunately due to space restrictions it was not possible to add all the repositories for each organisation, so some of the circles above relate to more than one project for the same organisation (e.g. MattyIce (bottracker) also includes work done on the postpromoter bot).

^{Apologies the text is a little small - in order the entries are:
utopian-io, steemit, busyorg, WordPress, facebook (react)
opencart, eSteemApp, GNOME (gimp), code-dot-org, Minecolonies
bitshares, magento, electron, FreeCAD, inkscape, stoodkev (SteemPlus)
phalcon, deveerei (steemplay), therealFlauwy (1UP), liferay, Microsoft (TouchDevelop)
dtube, Chainers (steepshot-web), audacity, MattyIce (bottracker), BeehiveForum
shopware, gornanization (1k), JefPatat (SteemMakers), geoserver, zaproxy
exoplatform, Zappl, gplcart, torvalds (linux), arduino
mcfarhat (various), openfoodfacts, Akintunde102 (various), aaroncox (steemdb), thelia
apache (openoffice), LLK (scratchjr), netuoso (pacman-steem), coorasse (Airesis),
myary (steemauto), cloh76 (WhaleSong)}

It is perhaps not surprising that the three largest projects to benefit, Utopian, Steemit, and busy.org are all steem blockchain platforms.

Over 2018, as utopian starts to draw in users from outside the steem blockchain, I would expect the central circles to reduce and rewards to diversify into projects from the wider open source world.

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6 Top 50 Users

Finally, a sunburst chart of the top 50 users by author payout for the Utopian platform over 2017.

A further layer of breakdown - the main category type under which they post - has also been added. The colours should tally with those used on the utopian site for each contribution type. The grey segments are various smaller contribution types combined.

It is worth noting that there is at least one limitations to this analysis:

• The amounts are expressed as per the payout values shown on steem platform sites - no conversion has been made to US$ or to Steem. The value of payouts can actually differ quite substantially from one month to the next, depending on the value of the underlying currencies.

^{top 50 users over 2017 - utopian.io}

A few highlights:

• The chart shows that the three top rewarded users all diversified into various different categories for their contributions.

• Four of the top ten users specialised mostly in translation, with two video tutorial creators, and two developers.

With the increased rewards for development I would expect the developers to start to dominate the top places on the rankings in 2018.

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7 Scripts

This was the main script used for the analysis.

/* SINGLE APP ANALYSIS by AUTHOR and MONTH - 2017 Full year */
SELECT
    Comments.author,
    Month(Comments.created) as [CommentMonth],
    IIF(isjson(comments.json_metadata) = 1, IIF(CHARINDEX('/', json_value(comments.json_metadata, '$.app')) > 0, SUBSTRING(json_value(comments.json_metadata, '$.app'), 1, CHARINDEX('/', json_value(comments.json_metadata, '$.app'))-1),json_value(comments.json_metadata, '$.app')), null) as [Application], 
    Count(Comments.author) AS [Posts],
    Count(distinct Comments.author) AS [DistinctCommentAuthor],
    count(Comments.parent_author) AS [ParentAuthor],
    count(distinct Comments.parent_author) AS [DistinctParentAuthor],
    sum(CONVERT(REAL,Comments.pending_payout_value)) AS [PendingPayoutValue],
    sum(CONVERT(REAL,Comments.curator_payout_value)) AS [CuratorPayoutValue],
    sum(CONVERT(REAL,Comments.total_payout_value)) AS [TotalPayoutValue]

FROM
    Comments (NOLOCK)

WHERE
    YEAR(Comments.created) = 2017 AND
    depth = 0 AND
    IIF(isjson(comments.json_metadata) = 1, IIF(CHARINDEX('/', json_value(comments.json_metadata, '$.app')) > 0, SUBSTRING(json_value(comments.json_metadata, '$.app'), 1, CHARINDEX('/', json_value(comments.json_metadata, '$.app'))-1),json_value(comments.json_metadata, '$.app')), null) = 'utopian'     

GROUP BY
    Comments.author,
Month(Comments.created) as [CommentMonth]
    IIF(isjson(comments.json_metadata) = 1, IIF(CHARINDEX('/', json_value(comments.json_metadata, '$.app')) > 0, SUBSTRING(json_value(comments.json_metadata, '$.app'), 1, CHARINDEX('/', json_value(comments.json_metadata, '$.app'))-1),json_value(comments.json_metadata, '$.app')), null)

Very similar scripts were used for the analyses by contribution type and organisation / repository and for the extraction of data by day. Briefly the small differences are:

• Changing from grouping by the month of the comment creation date to the exact date of comment creation allows the extraction by individual date. The author information is not required for this run (and the results would be very large by author and date)
• Use of type and repository.full_name label information for extraction and grouping in place of the month.

That's all for today. Thanks for reading!

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Posted on Utopian.io - Rewarding Open Source Contributors

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