Utopian.io - January 2018 Statistics

In this first study of the 2018 January 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. This analysis focuses on the January 2018 data with a comparison back to prior months.

There are four parts to the analysis:

• Overview of January 2018: An overview of the figures for January 2018 (daily individual author numbers, post numbers and reward payouts);

• 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 January 2018 showing those users that have had most financial success through the platform and their main categories of contribution.

---

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 Overview of January 2018

The Utopian.io project launched in September 2017 and showed rapid growth over the last three months of the year. By December 2017 it was the third largest application on the Steem blockchain ranked by total post payout, a ranking it maintained in January 2018. Utopian showed over 90% growth in author and post numbers from December to Janaury, rising from ninth to eighth ranking by number of posts, although slipping from sixth to seventh ranked by number of users posting articles due to the rise of dmania.

The chart below covers the last three months: November 2017 - January 2018 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.

^{Main metrics - Utopian}

The chart illustrates that whilst Utopian is still growing month on month, the exponential pace of this growth has slowed. This is mainly due to the changes made at the end of the first week of January - there was firstly a pause in contributions for the translations category, closely followed by rule changes which increased the quality requirements over all categories. The impact can be seen by the large dip around January 11. As can be seen, following this dip, contribution numbers rapidly recovered and moved back towards their previous highs.

The table of monthly figures for Utopian summarises the overall results by month:

Month	All Posters	Regular Posters	All Posts	Total Payouts
Oct	199	36	567	7,210
Nov	554	192	2,743	65,031
Dec	1,270	624	9,758	221,268
Jan	2,508	1,211	18,633	307,339
Total			31,701	600,848

The January figures showed 90% increases in regular author and post numbers and a 39% increase in reward numbers.

The figures also suggest an overall average payout of around $16 per article, down from $22 on average over 2017.

Looking forward to February it is likely that the further restrictions on translation contributions will have a significant impact on user and post numbers. Given the size of this category, will we see a reduction in overall numbers fro Utopian?

---

0.2 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 (section 0.2) and which projects are benefiting from this work (section 0.3).

The chart below shows post payouts (orange columns - excluding the utopian beneficiary payments) and post numbers (blue dots) for January 2018.

^{Breakdown by contribution type}

As was the case over 2017, the largest category for January 2018, both by popularity of contribution and by payout, was translations.

Ideas took over the second ranking by post numbers pushing tutorials down to third. Video tutorials rose from fifth to fourth at the expense of graphics.

Development became the second rank by rewards, buoyed by the promotion of double utopian upvotes. Video tutorials also rose, pushing tutorials down from second to fourth spot.

---

0.3 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).

The table below compares the January 2018 top assisted organisations to those from 2017.

Rank	Jan 2018	2017
1	steemit	utopian-io
2	facebook (react)	steemit
3	ancap-ch	busyorg
4	utopian-io	WordPress
5	dollar-street-pages	facebook (react)
6	zaproxy	opencart
7	opencart	eSteemApp
8	code-dot-org	GNOME (gimp)
9	SpongePowered	code-dot-org
10	curiousexpedition	Minecolonies
11	WordPress	bitshares
12	exoplatform	magento
13	bitshares	electron
14	Microsoft	FreeCAD
15	electron	inkscape
16	arduino	SteemPlus
17	PrestaShop	phalcon
18	phalcon	Steemplay
19	joomla	1UP
20	Minecolonies	liferay

The top 5 places in January 2018 were dominated by Steem platforms and by organisations receiving translation assistance. With the increased stringency on translations imposed in February it is possible that the rankings of these latter organisations will fall in future.

Steemit: Obtains the top rank thanks to having a spread of contributions across all categories, including heavy contributions from analysis and social.

React: A javascript library maintained with assistance from Facebook. 99% of the Utopian contributions were translations.

ancap-ch: Translation and publication (digital files) of libertarian and anarcho-capitalist text resources. 100% of Utopian contributions were translations.

utopian-io: As for steemit, benefitted from a spread across all categories, but with a very significant contribution from development.

Dollar street pages: The Gapminder Foundation project looks at how families live in different countries and their relative incomes. Again, translations were the main assistance provided.

---

0.4 Top 50 Users

Finally, a sunburst chart of the top 50 users by author payout for the Utopian platform over January 2018.

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 - utopian.io}

For comparison, top 50 users by author payout for the Utopian platform over 2017.

A few highlights:

• As expected, with the increased rewards for development we see a marked change in January 2018. The top right hand quadrant now includes 7 developers in the top 10 contributors, up from only 2 in 2017.

• We appear to be seeing greater specialisation with most of the top users focusing predominantly on one category (although this may be due to the shorter time period - 1 month vs 3 months).

• Translation still dominates with 23 out of 50 contributors specialising in this field in January 2018.

• My “name” is on this chart. Thank you! Your support is much appreciated!

I would expect the developers to increasingly dominate the top places on the rankings as 2018 progresses.

---

Outline

• 0 Summary of Findings and Conclusions (see above)
• 0.1 Overview of January 2018
• 0.2 Analysis by contribution type
• 0.3 Analysis by organisation and repository
• 0.4 Top 50 Users
• 1 Scope of Analysis
• 2 Tools Used
• 3 Scripts

---

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 built and maintained by @arcange, containing all the Steem blockchain data.

The Utopian data has been filtered from the overall steem blockchain data by two approaches:

• 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. This data was used in section 0.1 for consistency with other analyses that I produce.
• Use of the beneficiaries column information of the Comments table. This data is expected to be more complete and was used in sections 0.2 - 0.4. There was approximately a 5% difference between the two data sets.

The analysis focuses on articles posted in January 2018. 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.

---

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 in the next section.

---

3 Scripts

This was the main script used for the analysis.

/* SINGLE APP ANALYSIS by AUTHOR and MONTH - 2017 Full year */
SELECT
    Comments.author,
    YEAR(Comments.created) AS [YEAR], 
    MONTH(Comments.created) AS [MONTH],
    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) = 2018 AND
    MONTH(Comments.created) = 1 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,
    YEAR(Comments.created),
    MONTH(Comments.created),
    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!

---

Posted on Utopian.io - Rewarding Open Source Contributors

---