Statistics About How Whales Use Their Votes

in steemit •  8 years ago  (edited)

In order to add to the discussion of whale voting behaviors (the good, the bad, and the ugly), I dive into the data.

TLDR: Whales overwhelming vote UP content, only downvoting about 6.4% of the time. They also give a modest amount of attention to comments sections, using 14.6% of their votes on comments.

I wanted to add something to the ongoing discussion about voting behaviors (which typically revolve around WHALE voting behaviors in particular), so I thought a good first place to start was to simply mine for data and see exactly how whales are using their votes. I used a very simple code based on Piston to sift through the votes for many of the top accounts on steemwhales.com, ignoring those whales with little or no voting history. Overall I ended up pulling data from 31 of the top whales. Out off 21,850 votes that I found, 93.6% of those were upvotes, and 14.6% were used in the comments sections.


Overall Representative Whale Voting Behaviors

Next, I wanted to break this down by whale, to see how each one uses their votes specifically. Here you can see that, as expected, @wang has a flawless upvote record, and the majority of whales use more than 90% of their votes to upvote content. As you can see @dan and @dantheman are the only accounts that use more than 20% of their votes to downvote content. I think the proper way to interpret this is that Dan takes a more aggressive approach to finding and flagging inappropriate or plagiarized content. I leave it to the reader to form further conclusions from these results. Perhaps if this post sees modest success, I will dig into the data further and try to subjectively analyze whale's downvotes to qualitatively examine when those downvotes are used "for good" or "for evil".


Percentage Of Votes That Whales Use To Upvote Content

Finally, I wanted to look at how frequently Whales use their votes in the comments sections. As @dantheman was discussing yesterday, random voting in a comments section can be very profitable for whales. This is not to say that these votes are either random or purely motivated by profit, but it may be valuable to look at the trends nonetheless.


Percentage Of Upvotes That Whales Use In The Comments Sections

As you can see, @fuzzyvest, @summon, and @berniesanders top the charts for voting in the comments section. I leave it to you to form whatever conclusions you will from this. Personally, I enjoy the occasional random Bernie vote storm in a comments section. What do you think about?

If you are interested in the code that I used, it is here:

#! /usr/bin/env python3 
from piston.steem import Steem
steem = Steem()
voters = ['ned', 'dan', 'blocktrades', 'jamesc', 'berniesanders', 'smooth', 'val-a', 'dantheman', 'tombstone', 'itsascam', 'rainman', 'steemed', 'summon', 'blackjack', 'cloop1', 'pharesim', 'steempty', 'wang', 'firstclass', 'complexring', 'fuzzyvest', 'riverhead', 'abit', 'roadscape', 'steemit200', 'xeldal', 'wackou', 'arhag', 'enki', 'clayop', 'nextgencrypto', 'kushed', 'witness.svk', 'proskynneo', 'smooth.witness', 'silversteem']
voterIndex = 0
num_posts = 4000
upvotes = []
downvotes = []
numVotesOnComments = 0
x = steem.get_account_history(voters[voterIndex], end=100000000, limit=num_posts, only_ops=["vote"])
for index, item in enumerate(x):
      myItem = item[1]
      operation = myItem['op']
      opDetails = operation[1]
      voter = opDetails['voter']
      permlink = opDetails['permlink']
      weight = opDetails['weight']
      author = opDetails['author']
      if voter == voters[voterIndex]:
            msg = "Voter: " + voter + ", Author: " + author + ", Permlink: " + permlink + ", Weight: " + str(weight)
            if weight > 0:
                  upvotes.append(msg)
            else:
                  downvotes.append(msg)
            if permlink[:3] == "re-":
                  numVotesOnComments += 1
print("Whale = " + voters[voterIndex])
print("Total Votes = " + str(len(upvotes) + len(downvotes)))
print("Upvotes = " + str(len(upvotes)))
print("Downvotes = " + str(len(downvotes)))
print("Total votes used on comments = " + str(numVotesOnComments))

Hopefully this has been interesting and given you some new ideas for considering and forming your opinions about whale voting! Let me know what you think in the comments section below :)

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I am glad you could take time away from burninating both the peasants and the countryside to add some hard data to the whale voting debates.

Sometimes you've gotta step back from a life of nonstop burninating.

I appreciate the info though, I wouldn't have thought dan/dantheman were at 20% of votes to downvote things but I guess it makes sense if they really want to shape what sort of content is featured.

That's what I was thinking.

Time to put the random comment vote hypothesis to the test!

(ง ° ͜ ʖ °)ง

lol, good luck!

I'll need good fortune to make a fortune.

ᕕ( ಠ‿ಠ)ᕗ

looks good, keep 'em coming!

I have that effect on people.
( ͡~ ͜ʖ ͡°)

This was great, dont know this was posible to find out.

This realy give a great sign of why it is not so often whale votes on a coment.

-Regards

Everything is possible, the trick is just figuring out how to get the data from the blockchain :)

Nice. It is realy great to watch all the good programers, who actualy could use the breaking banking system.

I am glad to be a part of this revolution :)

There are a lot of people do amazing thing with all these new technologies!

  ·  8 years ago (edited)

Yess, allways something new. Wondering how the future would be :)

Statistics about Whales is wonderful, need to improve upvotes on commenting so that everyone who engaged in posts can be rewarded.

Thanks!

ah man, thanks for providing the code. now I have something to play with! cheers!

No problem! It's nothing fancy, but it did the job.

  ·  8 years ago (edited)

trogdor

excellent post.
I think you need to reconsider the structure of upvotes for whales.
upvote and follow you.

Thanks!

That's very interesting.. Is there an easy way that I could find out my upvote/downvote percentages without getting into all that code stuff?

Thanks! I just ran a quick test with your username. Out of the first 479 votes that I found, 93.7% were upvotes, and 23.4% were used on comments. Hope that helps :)

Oh cool, thanks! :)

That pleases me!

thank you for share this usefull piece of code

No problem, thanks for checking it out!

@trogdor upvoted and followed. Great article, very interesting. Great job hope to see more of this info in the future.I wish I knew how to write programs.
@halo xoxo

Thanks! I'll be sure to check out your page. :p

Not being more than an amateur weekend coder, the main thing I took away from this was: Overall I ended up pulling data from 31 of the top whales. Out off 21,850 votes that I found,
I mean WOW. Everyone I have read so far moaning and whining about Whale voting, has been about how little of their "love" is doing the rounds.
But this is like an average 704 votes each!!
There's a few ways of looking at this. So if the platform has 40-50k users in this time period, thats a 50% chance of receiving a Whale vote, all things being equal. Right? The question then is, are all things equal?
Btw, what timeframe is this over? A week? A month? Since Steemit started?
Even over 4 months, thats an average 6 votes a day, every day, for each of these Whales.
Man, people need to quit with the moaning and get with the creating great content of value that serves the community.
Here endeth the lesson :)

  ·  8 years ago Reveal Comment

GLAD you up voted me, that is how I found you. I wish more STEEMIT users did, it would be so much better for everyone. I am so glad you posted these numbers, I up voted, and will now follow as well. Thanks @trogdor
full $teem Ahead!
@streetstyle

Thanks for sharing.
Regards.