Blockchain Business Intelligence: Australia Tags Trend & Distribution

in #utopian-io7 years ago (edited)

Details

I've done this similar analysis for country specific tags for mostly developing nations, or countries of proximity to the Philippines. I thought about doing an analysis on performance of a country outside of the Asian continent, and from a first world. I started studying users from the United States and the United Kingdom, but am unable to figure out a common tag users from those countries are using as an identifier. I have found the parameters I wanted to study in the tags #australia, and #teamaustralia.

Presentation1.jpg

Outline

Here are the key points I covered in this analysis to show the trend, an interesting transition, and the distribution of payout for the tags #australia, and #teamaustralia.

Scope of Analysis

This analysis shows a 19 months worth of data to present trends and distribution. I generated the data to capture all information from inception in March 2016 till the time the data was extracted on February 4 (5:30 PM GMT). I removed the February 2018 data when presenting trends since that month will only have 3 days and 17.5 hours worth of data.

I have found some 1417 rows overlap between the Australia and TeamAustralia tags and called that out in the charts where I presented distributions between them. On charts where I showed top categories and authors, I limited the count to 25 so that the charts and labels will be clear and visible. The Top Authors were based only on posts where the Australia and TeamAustralia tags were used, and that is not a representation of their total rewards.

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.

I started with generating the data with #australia tag using this query:

SELECT *
FROM Comments (NOLOCK)
WHERE json_metadata like '%"australia"%'

The data returned just a little over 10,000 rows and I could not believe that it summed up all the activities for the Australian community. I looked at some of the top authors for other possible country identifier tags, and found the tag #teamaustralia. I ran this query which returned over 30,000 rows:

SELECT *
FROM Comments (NOLOCK)
WHERE json_metadata like '%"teamaustralia"%'

I then tried to figure out a way to run a query that will merge the two tags and capture the data related to both the tags, and ran this query which returned 39,348 rows:

SELECT *
FROM Comments (NOLOCK)
WHERE json_metadata like '%"australia"%' OR json_metadata like '%"teamaustralia"%'

In summary; the #australia tag returned 10,287 rows, the #teamaustralia tag returned 30,478 rows, the sum of the rows returned by both tags is 40,765, the combined query returned 39,348 rows. This means that there are 1,417 rows where both the tags were used. I am calling this overlap in this analysis.

I used the json_metadata column in this analysis to capture all the posts and comments where the #australia and #teamaustralia tags were used, even if they were not the primary tags used. The charts were created using Microsoft's Power BI.

Results

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Compared to all other country specific tags I analyzed, the #australia tag's been around the longest. The first post where #australia tag was used was seen as early as May 2016. The posting activity seem to have been flat for an entire year from May 2016. There was a breakthrough in June 2017 in terms of both posting activity and payout. Incidentally, the tag #teamaustralia was first used in June 2017.

Between June to December 2017 the posting activity and payout's been flat with minor disruption of trends associated with rises in the price of Steem in June and December. There was another breakthrough that happened in January 2018 on both the count of posts and the total payout.

Australia & TeamAustralia Trend Comparison

image.png

These two charts show the transition that happened in June 2017 between the #australia and #teamaustralia tags. Not only that more posts are being created using the #teamaustralia tag from its birth in June 2017, the support via upvotes is also significantly more for the tag, resulting to five times as high total payout value for the tag #teamaustralia compared to #australia

image.png

Unique Authors Count Trend

image.png

The growth in posting activities resulting to the increase in payout clearly has to do with the growth in trend of count of authors posting under the tags being analyzed in this contribution. Like in the other trends presented so far, the first breakthrough here is seen in June 2017 when the #teamaustralia tag was first used.

Distribution Between Posts & Comments

image.png

The ratio between posts and comments count in the combined #australia and #teamaustralia tag is almost one is to one. The distribution however, in terms of payout is a deviation from the system-wide distribution of 93% payout for posts, and 7% for comments. In this analysis the share of comments in terms of payout is only coming up to a little over 1%.

Post Payout Range Distribution

image.png

This chart shows the distribution of posts in pre-defined payout ranges. Contrasting this against an earlier analysis on the Nigeria Tag where a quarter of the posts got zero payout, this is a lot less in the #australia and #teamaustralia tags at 17%. Looking at a similar distribution specifically for the month of December 2017, the post with zero payout went even lower to 10%. 30% of the posts in these tags earned at least 5 in terms of total payout value, compared to only 21% in the #nigeria tag.

Top 25 Categories Used With Australia & TeamAustralia Tags

image.png

There seems to be some really strong drive to use and support the #teamaustralia tag. It is not being used simply as a tag, it is the most often used category (primary tag) as well. As shown in the chart it is also the number one category in terms of payout.

Top Authors By Payout When They Used Australia & TeamAustralia Tags

image.png

This chart shows the top most paid authors in terms of total payout value on posts where they used the #australia or #teamaustralia tags.

bridgetbunchy whose username was word-wrapped in the chart is an early adopter who joined in July 2016, and ausbitbank is a top Steem witness and known supporter of multiple communities. Like in the other country specific tag analysis I've done, I try to identify sndbox members from the top authors. In this analysis, I was only able to identify bearone who is my fellow cohort in sndbox, she is also an active officer and organizer of various communities including our steemph in the Philippines where she's from and teamaustralia in Australia where she lives.

Conclusion

While there are significant difference in terms of payout ranges, this is something that did not surprise me considering the economic condition of Australia in comparison to other countries I've done analysis on. The top authors in the #australia and #teamaustralia tags like in any other country specific tags I've studied are also the ones who are actively promoting Steemit, early adopters, and witnesses who are running multiple projects in support of the Steem blockchain.

While with only a little over 24 million population, Australia has great growth potential since over 95% of that population are connected to the internet. With steady economy, growth in Australia may very well mean fresh investments coming into the platform.



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Hey @steemitph I am @utopian-io. I have just upvoted you!

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Great research and analytics @steemitph :) thanks for sharing!

Wow! It's not everyday we get comments from @sndbox. Thanks for all your support. Glad you liked it.

Kumusta Red! :) interesting stuff there.. Its good to keep track and be watchful..

Yep. Thanks for your support sir @chinito. Been doing much analysis lately, trying to understand how this all work.

Great stats. Thanks.

@steemitph, nice stats!

However, you should NOT use SELECT * in your queries because you will retrieve ALL columns from the table, including the body column, which is absolutely useless for building your stats.

This kind of query uses a lot of resources and bandwidth, and negatively impacts responsiveness for other users.

I urge you to limit your SELECT clause to the columns you need for your stats.

Feel free to contact me on steemit.chat if you need any help.

Hi @arcange, copy this. I will spend time this week to study the table structures and limit my queries to the columns I need. Thanks for your awesome work on the SQL Database.

Congratulations! This post has been upvoted from the communal account, @minnowsupport, by steemitph from the Minnow Support Project. It's a witness project run by aggroed, ausbitbank, teamsteem, theprophet0, someguy123, neoxian, followbtcnews, and netuoso. The goal is to help Steemit grow by supporting Minnows. Please find us at the Peace, Abundance, and Liberty Network (PALnet) Discord Channel. It's a completely public and open space to all members of the Steemit community who voluntarily choose to be there.

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Detailed and briefly described good

Detailed and briefly described good