InfoSec Person | Alt-Account#2

  • 9 Posts
  • 73 Comments
Joined 1 year ago
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Cake day: September 28th, 2023

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  • Oh boy, this was a 20 minute rabbit hole.

    Tl;Dr: this is probably AI generated.

    Using google image search, I found is that it was created by this account in Oct/2024:

    https://www.instagram.com/gothtoon/p/DBh-p4WgThS/

    Alternative front-end: https://imginn.com/p/DBh-p4WgThS/

    There is the copyright symbol with this user in this image.

    If you go through the comments and other posts by that user, it does look AI generated. Their threads account has a linktree, which has a link to a discord server, which I momentarily joined to see what the deal is about.

    Looks like it’s a project started by a user named Emo Bot 9000, and they’ve created a bunch of characters, the most famous of which is the frog mage. This is a message on discord that supports this:

    Another user asks whether the frog mage stuff is made using AI, and Emo Bot 9000 essentially replies yes:

    Now, although the image in this lemmy post is, to the best of my searching, nowhere explicitly labeled AI, I think it mostly points to being generated by AI. The simplest way to confirm would be to ask them on their discord directly, which I don’t intend to do.

    Although reverse search tells me there are earlier appearances of this image, they’re either false or the PFP of a commenter.













  • That seems to be the consensus online. But thanks for that tidbit! It feels even more bizarre now knowing that.

    I wonder why a handful of people think the way I presented in the post. Perhaps American/British influences in certain places? Reading books by british authors and books by american authors at the same time? Feels unlikely.






  • My bachelor’s thesis was about comment amplifying/deamplifying on reddit using Graph Neural Networks (PyTorch-Geometric).

    Essentially: there used to be commenters who would constantly agree / disagree with a particular sentiment, and these would be used to amplify / deamplify opinions, respectively. Using a set of metrics [1], I fed it into a Graph Neural Network (GNN) and it produced reasonably well results back in the day. Since Pytorch-Geomteric has been out, there’s been numerous advancements to GNN research as a whole, and I suspect it would be significantly more developed now.

    Since upvotes are known to the instance administrator (for brevity, not getting into the fediverse aspect of this), and since their email addresses are known too, I believe that these two pieces of information can be accounted for in order to detect patterns. This would lead to much better results.

    In the beginning, such a solution needs to look for patterns first and these patterns need to be flagged as true (bots) or false (users) by the instance administrator - maybe 200 manual flaggings. Afterwards, the GNN could possibly decide to act based on confidence of previous pattern matching.

    This may be an interesting bachelor’s / master’s thesis (or a side project in general) for anyone looking for one. Of course, there’s a lot of nuances I’ve missed. Plus, I haven’t kept up with GNNs in a very long time, so that should be accounted for too.

    Edit: perhaps IP addresses could be used too? That’s one way reddit would detect vote manipulation.

    [1] account age, comment time, comment time difference with parent comment, sentiment agreement/disgareement with parent commenters, number of child comments after an hour, post karma, comment karma, number of comments, number of subreddits participated in, number of posts, and more I can’t remember.