Blockchain Business Intelligence: India Tag Trend & Distribution

Details

With a population of over 1.3 Billion, and nearly 35% of which have some form of access to the internet, India have a real potential to become a growth area in terms of Steemit user-base. According to Internet World Stats there are 251 Million Facebook users from India. The recent news about the Indian government stance on legalizing cryptocurrency, adoption of blockchain technology into their banking system, and the influx of interest from the Indian community towards bitcoin post the demonetization drive announced by PM Narendra Modi is creating a buzz about both cryptocurrency and blockchain adoption.

Existing interest in social media, developing curiosity about the blockchain and cryptocurrency, huge population, and on-line presence can very well lead to faster adoption of Steemit in India. This analysis will look at the current Indian community as part of Steemit user-base, the trend of adoption, and payout distribution using the tag #india.

Outline

This analysis will present data-points related to:

• 22 Months Trend In Terms of Count of Posts and Total Payout Value
• Engagement Shown in the Distribution Between Posts and Comments
• Payout Performance of Posts Using Pre-Defined Ranges
• Top Primary Tags in Terms of Payout
• Top Authors in Terms of Payout
• Growth Trend in Count of Unique Author over 22 Months
• A Scatter Plot of The User-base Using the India Tag

Scope of Analysis

This analysis covers the posts and comments where the #india tag was used from inception until the 28th of February. I ran the SQL query on the 3rd of March (Saturday) at 12NN GMT, but delimited the data to only include posts and comments created until the 28th of February.

In the user-base scatter plot, I excluded everyone with less than 10 posts using the #india tag, I have also made some specific exclusions of outlying dots. Here are the users I excluded:

• adsactly is described as and "Autonomous Decentralized Society". The account is know to be using country specific tags as a part of their campaign.
• anwenbaumeister is from a user from California, USA.
• firepower is an early adopter from India. His nearly whale level vesting share created an outlying dot.
• juvyjabian is an early adopter from the Philippines.

Tools

I used arcange's Steem SQL Database in generating the data. I used the Comments Table for the posts, comments, payout and language by running this query in a Microsoft Excel Spreadsheet:

SELECT author, category, parent_author, json_metadata, created, total_payout_value, pending_payout_value
FROM Comments
WHERE json_metadata like '%"india"%'
AND created>= CONVERT(datetime,'3/1/2016')
AND created< CONVERT(datetime,'3/1/2018')
GROUP BY author, category, parent_author, json_metadata, created, total_payout_value, pending_payout_value

In the Scatter Plot, I used the Accounts table and ran this query:

SELECT name, created, vesting_shares, reputation
FROM Accounts
GROUP BY name, created, vesting_shares, reputation

To get the simplified reputations score, I used this formula:

=ROUNDDOWN(MAX(LOG10(ABS(reputation))-9,0)*IF(reputation>=0,1,-1)*9+25,0)

The charts were built using Microsoft's Power BI.

Results

Majority of the country specific tags I studied only started showing up in July of 2016. The #india appeared as early as May 2016 as shown in the chart above. Adoption however, was rather slow, and really only started picking up a year later in June 2017. It was then again flat until another inflection happened towards the end of 2017. The huge swings in payout value in June and December 2017 is a function of the same swing that happened in the market price of Steem.

Distribution Between Posts and Comments in Count and Payout Value

This is one of the lowest engagement in comment I've seen in terms of comment to post ratio. This is 1:1 for the tag #australia for example. This can well be driven by the low level of appreciation given to comments through upvotes. In January I did a study on Comment Total_Payout_Value where I showed that system-wide, 93% of the author rewards goes to posts while the remaining 3% goes to comment.

Here the payout share for comments is much lower in comparison to the system average.

Post Payout Value Range Distribution

This is a really good story for the #india tag. Only a little over 7% of the posts had zero payout value. For comparison, zero payout is nearly 25% of the posts in the #nigeria tag and nearly 17% of posts in the #australia tag analysis I've done last month.

Later in the analysis, you would see that there's a handful of users who have accumulated dolphin level Steem Power, and because of which, they are able to support the #india tag.

Top 25 Categories Sorted By Payout Value

Looking at this chart, we will see that the authors using the #india tag are fond of short form contents. The tag #india is on top in terms of count of posts, while #photography is on top in terms of payout.

We can also see other photography related tags like #colorchallenge, #sevendaybnwchallenge, #smartphonephotography, and #steepshot.

Top 25 Authors Sorted By Payout Value

firepower and sauravrungta are both early adopters who've both been able to accumulate dolphin level Steem Power, firepower in fact is nearly a whale. geetharao at number three is firepower's dad who joined in June 2017, while travel-cuisine at number four is an Indian artist who joined in June 2017 and quickly escalated in reputation level after finding herself a number of whale supporters.

Unique Author Count and Payout Value Trend + Active User-Base Scatter Plot

The biggest opportunity here is much like the system-wide user-base; user retention. In the chart above you will see more than 9,700 unique authors who posted using the #india tag, the scatter plot below however will only show 685 dots when the data was delimited to only those who posted at least ten times using the #india tag.

Conclusion

Overall, the trend for the #india tag is promising. There is enough influencers to drive accumulation of Steem Power to continue to grow the Indian community, Indians are known for being thrifty, and generally handles their money better than most people in developing economies. That trait applied to their Steemit activities through accumulation of Steem Power, coupled with existing Steem Power holders within the Indian community to drive better retention which is already evident in the low percentage of posts getting zero payout; India can become a huge community is Steemit.

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Posted on Utopian.io - Rewarding Open Source Contributors

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