Most Voted Authors - Weekly Report of Aug. 30 - Sept. 5

This is my third analysis of the steem blockchain with Python.

Here I present fresh data - what happened between Aug. 30 and Sept 5 - in conjunction with last week's results. This way we can make an impression of how things progressed since then.

I would like to give specials thanks to: @bitcalm, @furion, @heimindanger, @trogdor and @xeroc for providing inspiration for the Python code behind this report.

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Most Voted Authors - August 30 - September 5

Here's how the process goes:

1. I took ~30 high-power voters (whales) from heimindanger's website.
2. I used Python to analyze their votes. I included only the votes made on posts (ignore comment votes: if permlink[:3] != "re-").

As said, I am only analyzing high-power votes here; they carry the heaviest of weight. Were I to include all the votes from all users, the numbers and graphs may probably look different (but I assume the payout/post would not). Here are this week's results:

Number of High-Power Votes Given - Table View

Number of High-Power Votes Given - Plot

Number of High-Power Votes Received by Authors - Table View

Number of High-Power Votes Received by Authors - Plot

Historic numbers of high-power votes given:

• total high-power votes given this week: 5407
• total high-power votes given last week: 6124
• total high-power votes given two weeks ago: 6076

The interpretation might be biased because of my forgetting to include @berniesanders into previous analyses; luckily someone mentioned it in a comment last week.

A few points:

• overall, whales seem to be consistent with their votes
• similar to last week, some authors have dropped from the list while others have joined it
• similar to last week, the top 5 has changed

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The Code

The python code behind this analysis is in my github. Use/modify/adapt it at your own discretion.

To-do:

• optimize the statistics by splitting votes into: upvotes and downvotes. Some of the authors could be on the list due to a mix of upvotes and downvotes - as was the case of some plagiarizers. This has to be clarified.

If you have ideas for other similar analytics, please suggest them below.

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To stay in touch, follow @cristi

#programming #steemit #analytics

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Cristi Vlad, Self-Experimenter and Author