Analyzing the CCommons.Art in Steem Blockchain

Through my first article in the analysis field I would like to thank @arcange who has developed Steem SQL server and @paulag which has made many writings about analysis and has become a place for me to learn. once again thank you very much

One month ago, exactly on 26 January 2018 at 21:06 my friend @alexandaravart created the first post for this creative commons project via @ccommons.art account . the goal of this extraordinary project is to inspire you to support amazing artists in the arts who use creative commons licenses with sound and resteem, as they give away their work for free, for all of us to use

If you missed the @ ccommons.art entry that made its first Wall of Fame, you can read it here

https://steemit.com/ccommonsart/@ccommons.art/wall-of-fame-creative-commons-content

The purpose of this analysis is to look at the extent of reach and define some voting behavior from @ccommons.art and post within the #creativecommons , #creative-commons ,and #ccommonsart
For this analysis I have taken data from the Steemsql database for 2018 only - you can find the full details of the query after the analysis.

Vote Analysis from @ccommons.art

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No of Authors	No of Vote	No of post
129	536	536

Let's take a look at this Daily Top Tost and Author in 30 days Charts

Since early 2018 @ccommons.art has selected 536 times for 129 different authors in 536 posts. Value of SBD $ Vote given in the form of direct reward not from vote value. the sound weight given 100%. Total Reward provided by @ccommons.art is $ 122 SBD

Conclusion

The ccommons.art project is ongoing and continues to reward good contributions, as the average post payments for this tag are still lower than Steemit in general. We hope this project will continue to work especially the @globalscool activity implemented by @jnmarteu with @alexandravart

The Data and Query

I used LYNQPAD to connect to the Steemsql database. The SQL query used to get the voting data from Steemsql was

SELECT *
FROM Txvotes (NOLOCK)
WHERE [voter] in ('ccommons.art')
 and YEAR (timestamp) = 2018

The query used to get the tranfer was

SELECT * FROM
TxTransfers (NOLOCK)
WHERE [from] in ('ccommons.art'

The query used to get the daily top post and author in 30 days was

select top 30
   author,
   count (author) as cnt,
   sum (net_votes) as votes,
   sum (pending_payout_value) as pending_payout_value
from
   Comments
where
   title <> '' and
   dirty = 'False' and
   category = 'creativecommons' and
   parent_author = '' and datediff (day, created, GETDATE ()) between 0 and 30
group by
   author
order by
   pending_payout_value desc

After collecting the data from the Sql query, I then used Microsoft excel to carry out calculations and analysis across the tables.

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Posted on Utopian.io - Rewarding Open Source Contributors

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