If you've got $500 laying around that you can't wait to spend on something totally pointless, you could always snag @diegorm222 (ID 3314630561) or @ThatDubstepDJ (ID 398479839). It doesn't matter which one you buy since they basically have the same followers.

cc: @ZellaQuixote
A third account, @Cryptocurrentcc, shares nearly all of its followers with @diegorm222 and @ThatDubstepDJ. A total of 79647 accounts follow all three, comprising at least 96.7% of each main account's followers. Very few are new accounts, which is also unusual.
.@diegorm222, @ThatDubstepDJ, and @Cryptocurrentcc are all older accounts that have been mostly purged of tweets prior to July 2021. Recent content is all cryptocurrency-themed. Despite their age, these three accounts gained almost all of their 80K-ish followers in summer 2021.
The 79647 accounts that follow all three of @diegorm222, @ThatDubstepDJ, and @Cryptocurrentcc are mostly older, many of which had been silent for years until early 2021. Old tweets were sent via a variety of apps, while new tweets were mostly tweeted via the Twitter Web App.
The recent Twitter Web App traffic began abruptly in late April, and the content is quite repetitive. Many of the repetitive tweets are replies, which in some cases have posted verbatim by hundreds or thousands of accounts. Cryptocurrency is a recurring theme.
In addition to the repetitive tweets and replies, the accounts in this network also engage in retweeting, and they largely retweet the same accounts (mostly large Arabic-language accounts).
More on the follow order by creation date plots used in this analysis (including source code):

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More from @conspirator0

26 Jul
It's a Monday afternoon, which is the perfect time to look at a pornbot network with a penchant attaching random emoji to its repetitive tweets. Also, it spam-followed a rather odd lineup of accounts. #MondayMotivation #Spamtastic

cc: @ZellaQuixote Image
This network consists of (at least) 27745 Japanese-language accounts, created in batches between June 1st and July 25th, 2010. All tweets posted by these accounts so far were (allegedly) sent via the Twitter Web App. None has ever liked a tweet. ImageImageImageImage
The accounts in this network are extremely repetitive, with the same tweets frequently duplicated verbatim (other than emoji) by dozens of accounts. The accounts' biographies generally include an invitation to chat with unknown parties on the LINE messaging app. ImageImage
Read 6 tweets
25 Jul
The accounts in the original "requesting faucet funds" botnet have all been suspended, but a fresh batch has arisen to take their place, and they've evolved (slightly). #SaturdaySpam

cc: @ZellaQuixote Image
The current incarnation of the "faucet funds" network consists of 1436 accounts created between July 19th and July 22nd, 2021. All accounts have zero likes and zero followers, and have sent all their tweets thus far via the Twitter Web App (allegedly). ImageImageImage
As with the previous version of the network, all 1436 accounts in the new botnet have sent exactly one "Requesting faucet funds" tweet. Unlike the previous version of the botnet, these tweets are not accompanied by links to a website.
Image
Read 4 tweets
19 Jul
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.

cc: @ZellaQuixote
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.)
Read 9 tweets
18 Jul
Rather ironically given its stated interest in "healthy conversations online" and "thriving engaged communities", @OpenWebHQ got many of its early followers from a duo of fake follower botnets. We've seen one of these botnets before; here's a look at the other.

cc: @ZellaQuixote ImageImage
This fake follower botnet consists of 4075 accounts created in large batches in July 2014. All accounts have lowercase names containing underscores, and usually digits as well. All have been dormant since late 2015 but (allegedly) tweeted via "Twitter Web Client" when active. ImageImageImage
Who does this fake follower botnet follow? Mostly commercial/promotional accounts belonging to a variety of businesses and entrepreneurs. Most of the accounts followed by the bots tweet primarily in English, although a few Arabic-language accounts turn up as well. Image
Read 8 tweets
12 Jul
Meet @aykacmis, @degismece, @anlamislar, @aykacti, @kayitlii, and @donmedim, a sextet of blue-check verified Twitter accounts created on June 16th, 2021. None has yet tweeted and all have roughly 1000 followers (and mostly the *same* followers).

cc: @ZellaQuixote
Two of these six accounts (@kayitlii and @aykacti) have photographs of people as their profile pics. Despite the presence of the blue verification checkmark, neither image is likely to depict the account holder as both images appear to be stolen.
These six newly-created verified accounts have 977 followers in common. One is @verified (which follows all blue-check verified accounts). The other 976 were all created on June 19th or June 20th, 2021, and all follow the same 190 accounts. #Astroturf
Read 12 tweets
10 Jul
It's #Caturday, so here's a freshly-made botnet tweeting cat videos because of course that's a thing.

cc: @ZellaQuixote Image
This botnet consists of 36 accounts created in July 2021. All 36 accounts have links to blogspot blogs on their profiles and GAN-generated profile pics. (GAN = "generative adversarial network", the AI technique used by thispersondoesnotexist.com to generate fake faces.) ImageImage
The current generation of GAN-generated face pics (at least unmodified ones) always have the primary facial features (especially the eyes) in the same position on every image. This anomaly becomes visually obvious when the images are blended together.
Read 9 tweets

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