Meet @El6YUlRJVNEFutr (permanent ID 1412134274762002436). Despite having been created just two weeks ago and having almost no content, it has somehow accumulated a large following consisting almost entirely of accounts that are at least seven years old.
Weirdly, almost all of @El6YUlRJVNEFutr's followers are older accounts, created in 2013 or earlier. The near-total absence of accounts that are even remotely new is a sign that this follower growth is extremely unlikely to be organic.
These accounts are part of a bulk follow network that followed a variety of accounts en masse over the last few weeks. (The followers from the network are highlighted in orange on the follow order by date range plots.)
Here are the accounts most frequently followed by the accounts in the network. Almost all of the accounts followed by the network are Arabic-language accounts. Most (other than @El6YUlRJVNEFutr) are established accounts with at least some content.
The accounts in this network all follow hundreds of accounts but have few or no followers of their own. Almost have Arabic display names and "KSA" as their profile location. Most of the accounts between 2014 and 2021, when they suddenly woke up and kicked into high gear.
For many of these accounts, their recent reawakening was accompanied by a makeover. At least 9107 had their display names changed sometime between March 2020 (when we captured data on a bunch of older Twitter accounts) and July 2021 - in all cases, to Arabic text.
Almost all of this network's content since it woke back up (1996877 of 1997387 tweets, 99.97%) is retweets, mostly of the same content. The network primarily amplifies large Arabic-language accounts, although two of the top three are exceptions: @justinsuntron and @BitTorrent.
This network showed one previous spike of activity back in August 2012, when it posted thousands of tweets about "photos" accompanied by shortened links. The shortened links lead to pages hosted on narod(dot)ru that no longer exist.
How did we find this network? It bestowed a few hundred retweets each on a series of recent @ARTEM_KLYUSHIN tweets about a tanker fire in Dubai, all of which received substantially more retweets than likes as a result. This is a sign of potential astroturfing, so we dug deeper.
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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
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.
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.
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
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.
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.
None of these chefs exist, as they're all AI-generated images. This hasn't stopped them from racking up lots of engagement on Facebook by posting AI-generated images of food (and occasional thoughts and prayers), however.
cc: @ZellaQuixote
These "chefs" are part of a network of 18 Facebook pages with names like "Cook Fastly" and "Emily Recipes" that continually post AI-generated images of food. While many of these pages claim to be US-based, they are have admins in Morocco per Facebook's Page Transparency feature.
Between them, these 18 Facebook "chef" pages have posted AI-generated images of food at least 36,000 times in the last five months. Not all of the images are unique; many have been posted repeatedly, sometimes by more than one of the alleged chefs.
Can simple text generation bots keep sophisticated LLM chatbots like ChatGPT engaged indefinitely? The answer is yes, which has some potentially interesting implications for distinguishing between conversational chatbots and humans.
For this experiment, four simple chatbots were created:
• a bot that asks the same question over and over
• a bot that replies with random fragments of a work of fiction
• a bot that asks randomly generated questions
• a bot that repeatedly asks "what do you mean by <X>?"
The output of these chatbots was used as input to an LLM chatbot based on the 8B version of the Llama 3.1 model. Three of the four bots were successful at engaging the LLM chatbot in a 1000-message exchange; the only one that failed was the repetitive question bot.
The spammers behind the "Barndominium Gallery" Facebook page have branched out into AI-generated video and started a YouTube channel with the catchy name "AY CUSTOM HOME". The results are just about as craptastic as you'd expect.
In this synthetically generated aerial video of a (nonexistent) barndominium under construction, the geometry of the roof changes, a blue building appears, and a tree vanishes, all in the course of just three seconds.
This AI-generated barndominium features a long AI-generated porch with some chairs on it. Exactly how many chairs there are depends on what angle you look at it from, however, as the chair on the left splits into three chairs as the camera pans.
Some observations regarding @Botted_Likes (permanent ID 1459592225952649221)...
First, "viral posts which don't result in follower growth and have very little engagement in the reply section" is not a useful heuristic for detecting botted likes. Why not?
cc: @ZellaQuixote
"Viral posts that do not result in follower growth" is not a valid test for botting, because posts from large accounts often go viral among the large account's existing followers but do not reach other audiences, resulting in high like/repost counts but little/no follower growth.
"Very little engagement in the reply section" doesn't work for multiple reasons (some topics spur debate and some don't, some people restrict replies, etc)
Hilariously, @Botted_Likes seems to be ignoring their own criteria, as many of the posts they feature have tons of replies.