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Conspirador Norteño Profile picture
@conspirator0
Apr 23, 2021 • 6 tweets • 5 min read • Read on X
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It's a great day to look at a network of #SEO/#DigitalMarketing spam accounts with GAN-generated profile pics. #SEOShenaniGAN

(GAN = "generative adversarial network, the AI technique behind the fake faces generated by thispersondoesnotexist.com and similar tools)

cc: @ZellaQuixote
This network consists of 24 accounts created between May 2019 and December 2020. All have GAN-generated face images as their profile pics. Presently, all 24 (allegedly) tweet via the Twitter Web App.
The current generation of GAN-generated face pics have the anomaly that the major facial features (particularly the eyes) are in the same pixel position on each image. This trait becomes easy to see when we blend the images together, as in this video:
This network's content is mostly retweets, and the accounts mostly retweet one another - 26806 of 33786 retweets (79.3%) are retweets of other members of the network.
The network's original content is mostly hashtag spam, occasionally containing links to blog posts on digital marketing/SEO ("search engine optimization"). The hashtags used are marketing/SEO related, with #SEO, #DigitalMarketing, #SMM, and #Marketing, and being the most common.
In addition to retweeting one another, the accounts in this network also follow each other profusely: each member of the network follows an average of 19 of the other 23 accounts in the network.

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More from @conspirator0

Conspirador Norteño Profile picture
Jun 6
Some thoughts on perennial pitfalls in news coverage of social media manipulation that frequently result in reporting on fake accounts/bots/etc being far less accurate and informative than it ought to be...

cc: @ZellaQuixote
conspirator0.com/p/journalism-i…
The most common problem with news articles about fake accounts: failure to include any examples of fake accounts or evidence of their inauthenticity. Any or all of these headlines might be accurate, but you can't tell from the articles, due to absence of evidence. Six headlines: "Pro-Gun Russian Bots Flood Twitter After Parkland Shooting", "Congress Probes Bot-Generated Social-Media Messages About E-Cigarettes", "Researchers: Nearly Half Of Accounts Tweeting About Coronavirus Are Likely Bots", "Nancy Mace's Former Staff Claim She Had Them Create Burner Accounts To Promote Her", "Nearly Half Of Donald Trump's Twitter Followers Are Fake Accounts And Bots", and "Nearly Half Of Biden's Twitter Followers Are Fake, Audit Shows"
A related issue: articles like the "Nearly Half of Biden/Trump's Followers Are Fake" and "Nearly Half Of Accounts Tweeting About Coronavirus Are Bots" pieces base their numbers on closed-source third party tools, which may or may not actually be detecting anything useful.
Read 6 tweets
Conspirador Norteño Profile picture
Apr 26
Does thanking, praising, or insulting an LLM-based chatbot affect the speed or accuracy of its responses to questions involving basic arithmetic? Let's find out!

cc: @ZellaQuixote
conspirator0.com/p/how-to-talk-…
For this experiment, Meta’s Llama 3.1 model was asked to add and multiply random numbers between 10 and 100, with six different wordings: polite, rude, obsequious, urgent, and short and long neutral forms. Each combination of math operation and wording was tested 1000 times. image containing 24 math questions with a bunch of robots in the background
Results: asking the questions neutrally yielded a faster response than asking politely, rudely, obsequiously, or urgently, even if the neutral prompt was longer. Overall, obsequious math questions took the longest to process, followed by urgent, rude, and polite questions. bar charts showing the average processing time for addition and multiplication problems asked with six different phrasings
Read 6 tweets
Conspirador Norteño Profile picture
Mar 8
Just for fun, I decided to search Amazon for books about cryptocurrency a couple days ago. The first result that popped up was a sponsored listing for a book series by an "author" with a GAN-generated face, "Scott Jenkins".

cc: @ZellaQuixote sponsored Amazon listing for the "Crypto Essentials" series by "Scott Jenkins", an author with a GAN-generated face>
screenshot of the About the Author page for "Scott Jenkins"
Alleged author "Scott Jenkins" is allegedly published by publishing company Tigress Publishing, which also publishes two other authors with GAN-generated faces, "Morgan Reid" and "Susan Jeffries". (A fourth author uses a photo of unknown origin.) screenshots of the About the Author pages for "Morgan Reid" and "Susan Jeffries"
list of books by "Scott Jenkins" on the Tigress Publishing website
list of books by "Morgan Reid" on the Tigress Publishing website
Image
As is the case with all unmodified StyleGAN-generated faces, the facial feature positioning is extremely consistent between the three alleged author images. This becomes obvious when the images are blended together. all three GAN-generated faces blended together
Read 5 tweets
Conspirador Norteño Profile picture
Feb 8
The people in these Facebook posts have been carving intricate wooden sculptures and baking massive loaves of bread shaped like bunnies, but nobody appreciates their work. That's not surprising, since both the "people" and their "work" are AI-generated images.

cc: @ZellaQuixote three Facebook posts featuring AI-generated images of various large sculpted items: a loaf of bread shaped like a rabbit, and wooden sculptures shaped like a deer and an eagle
In the last several days, Facebook's algorithm has served me posts of this sort from 18 different accounts that recycle many of the same AI-generated images. Six of these accounts have been renamed at least once. collage of 18 Facebook profiles
Page Transparency info for six of the pages
The AI-generated images posted by these accounts include the aforementioned sculptures, sad birthdays, soldiers holding up cardboard signs with spelling errors, and farm scenes.

The common element: some sort of emotional appeal to real humans viewing the content. three Facebook posts featuring AI-generated images of various large sculpted items: a loaf of bread shaped like a rabbit, and wooden sculptures shaped like a deer and an eagle
three Facebook posts featuring AI-generated images of people holding birthday cakes
three Facebook posts featuring AI-generated images of soldiers holding cardboard signs with spelling errors
three Facebook posts featuring AI-generated images of people holding freshly picked produce
Read 7 tweets
Conspirador Norteño Profile picture
Jan 24
As Bluesky approaches 30 million users, people who run spam-for-hire operations are taking note. Here's a look at a network of fake Bluesky accounts associated with a spam operation that provides fake followers for multiple platforms.

cc: @ZellaQuixote screenshots of 12 Bluesky accounts with the biography "Praticante de esportes radicais"
This fake follower network consists of 8070 Bluesky accounts created between Nov 30 and Dec 30, 2024. None has posted, although some have reposted here and there. Almost all of their biographies are in Portuguese, with the exception of a few whose biographies only contain emoji. hourly creation volume chart for the 8070 accounts in the spam network
table of 30 example spam accounts
The accounts in this fake follower network use a variety of repeated or otherwise formulaic biographies, some of which are repeated dozens or hundred of times. Some of the biographies begin with unnecessary leading commas, and a few consist entirely of punctuation. table of biographies most frequently used by the network
screenshots of six accounts with malformed biographies
Read 8 tweets
Conspirador Norteño Profile picture
Jan 10
It's presently unclear why, but over the past year someone has created a network of fake Facebook accounts pretending to be employees of the Los Angeles Dodgers. Many of the accounts in this network have GAN-generated faces.

cc: @ZellaQuixote Screenshots of the profiles of 12 fake LA Dodger employee Facebook accounts
This network consists of (at least) 80 Facebook accounts, 48 of which use StyleGAN-generated faces as profile images. The remaining 32 all use the same image, a real photograph of a random person sitting in an office. collage of 48 GAN-generated faces used as profile images by the fake accounts
collage of 32 identical photos used as profile images by the fake accounts
As is the case with all unmodified StyleGAN-generated faces, the main facial features (especially the eyes) are in the same position on all 48 AI-generated faces used by the network. This anomaly becomes obvious when the faces are blended together.
Read 6 tweets

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