First up is @FarteenHu, an #ULTRAMAGA account with a GAN-generated face, a flatulence joke for a display name, and a bad habit of falsely claiming that COVID vaccines have killed over a million Americans. Note the unrealistic background, clothing, and headgear on the "face" pic.
Next, we have @atouchofsnark, an automated account with a GAN-generated profile pic that apparently intends to vote for Hillary Clinton, who is not currently running for office. This account's tweets are highly repetitive and posted via a custom app called "A Touch Of Snark".
Third up is @AbbyBrownJD, an alleged academic and activist with a GAN-generated face pic and a banner image featuring the face of journalist Taylor Lorenz. Although theoretically a Biden supporter, many of the account's tweets about Biden are farcical nonsense.
GAN-faced academic @AbbyBrownJD has had quite the busy life, including 8 years of education school, 3 years of teaching, 7 years as a gender studies professor, and multiple years of law school before age 33. Next up: a consulting gig in Ukraine related to "Natural Gasoline".
Fourth, we have @GoingRowan, a transphobic troll account with a GAN-generated face. In an interesting twist, @GoingRowan (permanent ID 1511352371829428239) was previously named @/CardenaCarey, and used a completely different GAN-generated face pic. archive.ph/MtBw7
Fifth up: @Comply2Resist, an alleged "tech company analyst" with a GAN-generated face and a penchant for anti-vaccine propaganda. This account also has something of a history with name changes...
The account currently named @Comply2Resist (permanent ID 1426363741159952391) has had at least two previous names: @/D4rkBlight and @/doctorwattsisin (which appears to have used a stock photo of a doctor, based on replies). web.archive.org/web/2021101006…
Finally, we have @TheRealJVanWyck. In addition to the current GAN-generated face pic, this "real" account has previously used at least three stolen profile photos.
There are a variety of signs that these images are GAN-generated: nonsensical clothes/backgrounds/headgear/glasses/teeth, identical eye placement, mismatched earrings, etc.
(The eye placement anomaly is obvious in the video at the top of this thread:
Here's a brief history of the #NationalDivorce hashtag. First used almost a decade ago by obscure accounts, it has in recent years been tweeted by a ragtag lineup that includes #Calexit founder Louis J. Marinelli and QAnon Congresswoman Marjorie Taylor Greene.
The first tweet containing #NationalDivorce appears to be a November 2012 tweet from @RTsolideogloria, a now-dormant right-wing account. This was later followed by several tweets in 2013/2014 from left-wing account @StrongAmerican encouraging Texas to secede from the USA.
In 2017, right-wing pundit and Claremont Institute fellow @davereaboi began using the #NationalDivorce hashtag somewhat regularly. His tweets containing it were largely ignored until June 2020, however.
Meet @BuyFollowers_pe, the "official" Twitter account of yet another shady website selling followers/likes/etc for a variety of social media platforms.
(As always, buying followers is unwise, and caution is recommended when visiting untrustworthy websites)
The website promoted by @BuyFollowers_pe, penmowu(dot)com, offers impressively large quantities: one can get up to 200K Twitter followers or 1 million Facebook likes in a single purchase. Interestingly, the website also sells scraped data, such as Twitter follower lists.
Unsurprisingly, the @BuyFollowers_pe account's followers do not look organic. The majority are new, empty accounts, with occasional older accounts thrown in (most created after 2014). All of @BuyFollowers_pe's followers followed it at more or less the same time.
Groups of spammy Twitter accounts downplaying human rights abuses in Xinjiang have been a recurring thing for the last couple years. Here's a look at a network of recently-created accounts spamming the #UyghurGenocide hashtag with content unrelated to genocide.
This network consists of 48 accounts created in early July 2022, mostly on July 5th. All have names consisting of a first name and a 3-5 digit number (usually at the end but occasionally in the middle), and all tweet exclusively via the Twitter Web App.
Almost all of this network's content (229 of 238 tweets, 96.2%) is repetitive "feel-good" tweets about Xinjiang (pretty pictures etc) that contain the hashtag #UyghurGenocide but are otherwise unrelated to genocide. Most of these tweets also contain the hashtag #Xinjiang.
When you're making a bunch of spammy accounts, you sometimes repeat generic biographies like "Type in your bio section & put the words that can aptly reflect your business" over and over. It's what you do.
These accounts are part of an astroturf network consisting of 1666 accounts created in batches from July 2021 to April 2022. Most have Turkish display names, and all of them post all of their tweets via Twitter for Android.
(Some of the accounts do have unique biographies.)
The accounts in this network have posted no original content whatsoever; all of their tweets to date are retweets. They most retweet cryptocurrency/NFT content, with occasional exceptions.
First up, we have @DrAdamAneevit, an antivax account with 38K followers and a GAN-generated face. Although this account's bio states that it is a "pArOdY", plenty of people are eating up its misleading tweets about COVID and vaccines.
As it turns out, @DrAdamAneevit (permanent ID 949263131800424449) wasn't always called @DrAdamAneevit. Wayback machine archives reveal that this account was previously a "news" account named @/ForFactsSake101.
This follower sales website, cryptolikez(dot)com, has an associated Twitter account by the name of @cryptolikez (permanent 1494042375529938946). Almost all of @cryptolikez's 41K followers are accounts created between March and June 2022 that followed @cryptolikez en masse.
The batch-created accounts following @cryptolikez are part of an astroturf botnet consisting of (at least) 243586 accounts created between January and July 2022. All of the tweets posted by this botnet were (allegedly) tweeted via the Twitter Web App.