Details
When the explore section of Steemit is sorted by payout, #kr is the only country specific tag that made it to the top enough to be displayed on screen without the need to scroll down.
At the time of the analysis, Alexa's global ranking of Steemit is 1352. The in country ranking in South Korea however is 181.
In this analysis I will try to present the trend and distribution of posts, comments and total_payout_value.
These are the tags that were used for this analysis #kr, #kr-art, #kr-newbie, #kr-join, #kr-writing, #kr-event, #kr-travel, #korea and #coinkorea. The analysis gave more emphasis however on the identified Top 3 korean tags #kr, #coinkorea, and #kr-newbie.
Outline
To briefly give you an idea on how the data will be presented, this analysis will be covering these topics:
- The post count, and total_payout value on posts distribution between the tags #kr, #kr-art, #kr-newbie, #kr-join, #kr-writing, #kr-event, #kr-travel, #korea and #coinkorea.
- The monthly distribution trend of total_payout value on posts between the tags #kr, #korea and #kr-newbie
- The comment count, and total_payout_value on comments for the tags #kr, #korea and #kr-newbie separately
- The Top 20 Authors based on total_payout_value on posts or the tags #kr, #korea and #kr-newbie separately
Scope of Analysis
I generated the data to present the distribution of total_payout_value between posts and comments from inception in March 2016 to January 14, 2018 (Sunday 12NN GMT). In the charts however that require showing trends, I left the January 2018 data because the data is not yet complete. I did that to avoid showing a skewed trend-line.
In the charts where I showed top authors and parent authors, I am only showing the top 25, beyond that count will be extremely difficult to put in charts without negatively affecting the look and feel, and clarity of the information when done in excel.
Unlike in the three earlier analysis on country related tags for Philippines, Malaysia and Indonesia; I am including the bit about the comments in this analysis. The tag #kr is Top 12 when the explore section is sorted by payouts, but it is Top 1 when sorted by the count of comments.
Tools
I used arcange's Steem SQL Public Database to acquire the data-points related to the count of comments, posts, total_payout_value, author, and parent_author.
In previous contribution with similar nature, I was downloading the entire table delimiting it by the category. Considering the size of the data involved on this one however, I chose to run a query in a pivot table using this:
SELECT
DATEADD(MONTH, DATEDIFF(MONTH, 0, created), 0) AS [year_month_date_field], author, parent_author, category, COUNT (total_payout_value), SUM (total_payout_value)
FROM Comments
WHERE category in ('kr', 'korea', 'kr-newbie', 'coinkorea', 'kr-event', 'kr-travel', 'kr-join', 'kr-writing', 'kr-art')
GROUP BY created, author, parent_author, category
I added the parent_author column to use as filter between parent posts and comments. By filtering the parent_author to only "blank" shows the posts, and by selecting everything else but the blank shows the comments.
I manipulated the pivot table in excel to get the distribution between posts and comments, by author to get the Top 25 most rewarded for posting and commenting, and by month to get the trend related information.
I used the basic charting tool in excel to plot the data into graphs and present the results of the analysis visually.
Results
Like in an earlier contribution about the global distribution of payout between comments and posts, the distribution for Korean tag is very much the same; 93% of the payout goes to posts, and 7% goes to comments.
Distribution Between the 9 Known Korean Tags
Between the 9 tags that are subject of this analysis, #kr seems to be the main one having considerable dominance at 89%.
As mentioned earlier, more emphasis will be given to the Top 3; #kr (89%), #coinkorea (6%), and #kr-newbie (3%). Together they made up 98% of the payout for posts with Korean tag.
The chart below shows that from July 2016 till March 2017 out of the Top 3 tags identified it was only #kr that was being used. #coinkorea started in April 2017, followed by #kr-newbie the following month.
Top 3 Tags By Payout Trend
There is a general uptrend in Payout performance in all the Top 3 tags with some anomaly in the months of June and December 2017 related to some spike in the price of Steem as pointed out in an earlier contribution.
Top 25 Authors by Payout
The below chart shows the count of posts and the total_payout_value on posts of the Top 25 authors using the combination of all the 9 tags which are subject of the analysis. In the Malaysia and Indonesia tags analysis I identified Sndbox fellows part of the top authors, in this analysis however, none of the Top 25 are Sndbox fellows.
I have added more information related to the Top 10 authors in the table below. It shows that out of the Top 10, there is one with more than 500K Steem Power, 3 with more than 100K Steem Power, and 3 with more than 10K Steem Power.
| Author | Reputation | Age (Months) | Steem Power |
|---|---|---|---|
| oldstone | 71.7 | 19 | 135,366 |
| leesunmoo | 72 | 22 | 558,909 |
| gotoperson | 67.8 | 15 | 108 |
| twinbraid | 68.6 | 18 | 15,770 |
| yoonjang0707 | 70.9 | 20 | 1 |
| clayop | 72.6 | 23 | 173,843 |
| virus707 | 71.1 | 7 | 168,130 |
| corn113 | 69.6 | 10 | 58,063 |
| snow-airline | 67.1 | 7 | 3,022 |
| kim066 | 66.3 | 8 | 30,698 |
Top 25 Commentors by Payout
This chart shows the Top 25 commentors sorted by total_payout_value for their comments on the 9 tags that are subject of this analysis. This shows a lot of engagement through comments on these tags. kimsungmin for example had 17,568 comments on posts with the 9 tags being analyzed in this contribution. With his account created in June 2017, this means an average 2,500+ comments per month or 83+ comments per day.
This analysis is the most interesting for me out of the ones that are similar in nature. In contrast with the same analysis for Philippines, Malaysia, and Indonesia related tags; Korea tags have more engagement in comments, their authors hold more Steem Power, and their tags are more organized with categorization.
It is also known to the whole community that the Korean community is quite precious about the use of their tags, which is the same reason I did not use any Korea tags in this contribution like I normally would.
Posted on Utopian.io - Rewarding Open Source Contributors