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.
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.
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.
Here are follow order by creation date plots for a bunch of the accounts followed by the botnet. The influx of bot followers shows up as a horizontal streak (highlighted in orange for clarity). Additional streaks related to other botnets are visible in a few of the plots.
The vast majority of this botnet's tweet content is retweets, mostly in English. What little "original" content the network has posted is tweets in Russian that are generally repeated across multiple accounts. (As always, take the Google translations with a grain of salt.)
Who did this botnet retweet back when it was active? As with the accounts it follows, the accounts it retweets are mostly promotional in nature, although they're a different set of accounts than the accounts followed, with something of a focus on tech/social media.
Here's a thread on the other botnet that @OpenWebHQ got some of its early followers from. (Portions of this botnet have been suspended by Twitter.)
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.
As with the banned @emywinst account, the @kamala_wins47 account farms engagement by reposting other people's videos, accompanied by bogus claims that the videos have been deleted from Twitter. These video posts frequently garner massive view counts.
@Emywinst @kamala_wins47 The operator of the @kamala_wins47 account generally follows up these viral video posts with one or more replies advertising T-shirts sold on bestusatee(dot)com. This strategy is identical to that used by the banned @emywinst account.
What's up with all these similarly-worded enthusiastic posts about a Pierre Poilievre rally in Kirkland Lake, and are they all from accounts that are less than a month old? (Spoiler: yes, they are.) #Spamtastic
cc: @ZellaQuixote
An X search for "Pierre Poilievre", "Kirkland Lake", and "refreshing" performed on August 4th, 2024 turned up 151 posts from 151 accounts. All are new accounts, with the oldest having been created less than a month ago, on July 7th, 2024. (Some have since been suspended by X.)
The most intense period of activity for this group of accounts was on August 3rd, 2024, when the repetitive posts about the Poilievre rally were posted. Each account also has at least one earlier post on a random topic; some of these older posts seem to cut off abruptly.