Here's a network graph for a popular hashtag. Since the graph has no labels, you can't tell what hashtag it is, or what anything in the graph actually means, but it's colorful and pretty and weird and therefore incredibly tempting to retweet, right?
The hashtag in question is #CatsOfTwitter, and here's a more boring-looking version of the same graph with more context. The interaction being graphed is retweets, with the more frequently-retweeted accounts shown larger on the graph, and the date range is also included.
One can alter the apparent meaning of a graph via manual editing. Here, three of the accounts have been dragged off to the top left, suggesting a relationship between them that isn't supported by the underlying data. It's technically still "correct", but it's misleading.
Graphs can also be misleading if one highlights a particular aspect without exploring it. Here, the retweets from bots (automated accounts) have been colored pink, revealing what appears to be a cluster of automated activity. Is this some kind of nefarious #CatsOfTwitter botnet?
Nope. Changing settings so that the label size is proportional to the number of times the account retweeted a #CatsOfTwitter tweet (rather than the number of times the account was retweeted) reveals that almost all of the automated activity is from just two accounts.
Overall point: while data visualizations are very useful and effective (and sometimes pretty) ways of summarizing lots of data, context is vital to interpreting them and should always be included.
Footnote: for this portion of the thread, automation was determined based on the source app used to post the tweet/retweet as provided by the Twitter API.
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.
• Community Notes successfully placed fact checks on some of the most viral false posts about the shooting
• ~42% of noted posts were subsequently deleted by their authors
• An effort to spread a misidentification of the shooter via Community Notes failed
THE BAD:
• Community Notes fact checks take several hours to show up, which doesn't help much in the initial "breaking news" phase after a violent event
• Many notes never accumulate enough ratings to determine their fate
12 questions for @TheDailyBeast regarding @JakeLahut's false April 2023 story, "How Ron DeSantis Is Taking a Page Out of Nixon’s Playbook", which (among other things) falsely portrays an AI-generated face as a "sexually graphic meme" of a real child.
@JoannaColes @TracyConnor
First, some background and a couple debunks of the false article, for those unfamiliar with the situation:
1. How did the decision to use serial fabulist Steven Jarvis as a source for this article come about?
2. Was anyone employed by or affiliated with The Daily Beast at the time the article was published aware of Steven Jarvis's extensive history of making false claims?
Meet @LovewinnLove (permanent ID 2707213009), a blue-check verified account with a GAN-generated face and a few additional odd characteristics. Despite being created in 2014, this account has no posts prior to October 2023.
cc: @ZellaQuixote
There are multiple indicators that @LovewinnLove's "face" is GAN-generated:
• unrealistic teeth (visible portion of bottom teeth is especially bizarre)
• odd texturing and seams in shirt fabric
• telltale eye positioning (more info in next post)
@LovewinnLove All unmodified StyleGAN-generated face images have the property that the major facial features (particularly the eyes) are in the same position on each image. Blending @LovewinnLove's profile image with 99 other GAN-generated faces demonstrates this nicely.
It's New Year's Eve, and a bunch of politics enthusiasts with GAN-generated faces are enthusiastically replying to a variety of posts with similarly-worded replies. #NewYearShenaniGANs
cc: @ZellaQuixote
The politics enthusiasts are part of a spam network consisting of (at least) 575 accounts created between May and December 2023 with GAN-generated faces. Many of their handles, such as @Maairiuieinaaa and @eJooeiaAoneueer, contain long strings of vowels.
@Maairiuieinaaa @eJooeiaAoneueer All 575 of these accounts use StyleGAN-generated faces as profile images. Some of these, such as @MauMoiagaia's profile image, contain a tiny "StyleGAN 2 (Karras et al.)" watermark in the lower right corner.
It's a great day to look at a network of inauthentic accounts that post identical AI art images (with a side of good old fashioned T-shirt spam).
cc: @ZellaQuixote
This network consists of 24 X accounts. 12 of these accounts were created in the latter half of 2023 and have female avatars, while the other 12 were created in 2013 or earlier and have male avatars.
The 12 accounts with female avatars and 2023 creation dates regularly post AI-generated art images, and these image posts are quickly reposted by other accounts in the network (both female and male). The AI-generated images are often duplicated across accounts.