I& #39;ve done two big in-depth studies of QAnon networks, one in 2018 (after D5 fizzled) and one in 2020 (in conjunction with Out Of Shadows). I want to share some more evidence to support Marc-Andre& #39;s argument here that Q posters are "bot-like" but not bots 1/ https://twitter.com/_MAArgentino/status/1293204041032499201">https://twitter.com/_MAArgent...
This is what a QAnon network on Twitter looks like: a bunch of individuals scattered around the periphery, but with a large, dense core that interacts with each other dozens of times per day.
I& #39;ve looked at a lot of Twitter networks, and Q ones always have the densest cores. 2/
I& #39;ve looked at a lot of Twitter networks, and Q ones always have the densest cores. 2/
In the D5 (Dec. 5, 2018) data I gathered, there were a small number of superusers who dominated interactions in the network. these are the users that I would describe as "bot-like" but research didn& #39;t support the conclusion that they actually were bots. 3/
In that last diagram, PrimeCreator2 tweeted at a handful of other users at LEAST 925 times on Dec. 5. Over the entire dataset of 56k tweets, PrimeCreator2 @-ed others 46,000 times, amounting to 233 unique users. 4/
These high-frequency superusers achieved extraordinarily high "betweenness" in the network, indicating that they are the information "bridge" between multiple different Q sub-communities. This is one way that Q users can game engagement and amplify their messages. 5/
You can read both of my Q network posts for more:
D5: https://rpubs.com/alexbnewhouse/net_qanon
Out">https://rpubs.com/alexbnewh... of Shadows: https://rpubs.com/alexbnewhouse/outofshadows">https://rpubs.com/alexbnewh...
D5: https://rpubs.com/alexbnewhouse/net_qanon
Out">https://rpubs.com/alexbnewh... of Shadows: https://rpubs.com/alexbnewhouse/outofshadows">https://rpubs.com/alexbnewh...