RE: Steem Sincerity - Update and Community Involvement

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Steem Sincerity - Update and Community Involvement

in steemdev •  7 years ago  (edited)

I am giving all the support that I can.

You must excuse if I do sound a bit salty, but the top-8 spammer classification has brought a lot of negative attention to an otherwise positively received project of mine.

But in all of this, I didn't take any offense and as a matter of fact i am encouraging users to try steem plus and help provide human feedback

If there's anything else I could do to help, I will.

I'll say it again. I explicitly support the steem sincerity project. I believe it is a great addition to the steem ecosystem.

It's just that I experienced a negative backlash from an (imho) false classification of my bots and as such I try to provide feedback and hope to illustrate the urgency of improving this asap because it is already being publicly used.

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Hi @andybets

I was hoping you can help me. Possibly something in a setting I need to change. Thanks in advance for any help!

I posted the below in a different article

"I just watched a really cool video by @exyle where he talks about the SteemPlus Chrome plugin. After learning about the new features I downloaded it straightaway. To my disappointment I am marked as a Spammer rather than a human. I have never spammed anyone so I was wondering how this could be and is there anyway I can change this mark?
Thanks
Dave @exploringirish"

Marking.png

  ·  7 years ago (edited)

You've replied to my comment here, so @andybets might not neccessarily see this comment of yours unless he has some sort of notification service he checks.

For now there's little that can be done as far as I understand the system. The AI gives you the score based on a machine learning algorithm and "comparing" your account data to what it "knows". This can be very misleading and equally inaccurate but an AI's algorithm is automated to a high degree and it's rather impractical to modify it's method of classification to a specific individual account.

If your account gets added to the training data as a "human", the AI might learn to distinguish your "data pattern" from what it currently knows as a "spammy" pattern.

P.S.: i just checked your detailed sincerity-API data and you're already scored as 57% human, either your account data changed for your benefit or the machine has learned since then.

Apologies for the incorrect classification scores. I have added you account to out system as an example of a human content creator, so it learns from this and improves in future.

Unfortunately, the SteemPlus feedback is proving problematic for various reasons. For example many people see a foreign language post, and report it as spam, or see bots and report them as spam. Basically many people are just using the classification to apart their own values, rather than actually considering whether the content is bad for the platform. So one reason for the delay in improvement is because any classifier however well designed is only as good as the data it is trained upon.

I appreciate your honesty anyway, and am working hard on this difficult problem.

  ·  7 years ago (edited)

Yeah, that seems to be a pitfall for "human-trained-AIs" ever so often... and then they turn into trolls themselves :(

Maybe you could ask for some "targeted" training evaluation of specific accounts via discord or so?! I guess some sort of human vetting of the resulting training set (and resulting AI behavior) cannot be foregone... Then again... maybe the "flat" account data just doesn't contain enough pointers for a reliable AI decision?!?

If I may make a suggestion, for the top-500, wouldn't it make sense to preselect a hierarchy based on comment/post-count, possibly filtered by incoming vote-diversity (to push voting-farm-spam to the top) and THEN classifying the spammer-probablity with the AI?!

just an idea... right now the leading criteria for the top 500 is the AI probability followed by comment-count... and that's awkwardly not including those real spam-heroes

P.S.: if that's not the case yet, maybe adding some of the really severe cases like a-0-0 with 25.000 comments to the training data as a top match for 1.0 spammer can help?!