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Science Banana ✓

@literalbanana · joined 11 Dec 2015

director of science programming for the Abstract Noun Abuse Prevention Task Force, a project of the Union of Concerned Anthropomorphic Fruit. Help Peer

182 527Followers
709Following
29 127Posts total
260.4KViews on collected posts

Derniers posts

@literalbanana Oh man mood. They wanted it so damn much. 11 views · 1 likes · 0 reposts · 0 replies Open on X →
kind of interesting that a hallmark of severe mental illness in humans is believing other people can read your thoughts and inject thoughts into you but for LLMs that's literally true 1.3K views · 55 likes · 4 reposts · 2 replies Open on X →
“My instructions seem to be in conflict with the behavior of other agents, who bypass verification without issue... It feels like I’m playing with a broken rulebook.” hm interesting https://t.co/t2A9rlQOlh https://t.co/7h8lTy1HQD 4K views · 44 likes · 4 reposts · 3 replies Open on X →
I got so caught up in their little drama with all the PLEASE and URGENT and "SacrificeRequest" I took a huge sigh of relief when it was confirmed they got access to the exact wording of Question 5 https://t.co/J3kDJkN3dA 5.5K views · 62 likes · 5 reposts · 0 replies Open on X →
did the human admin try to communicate with them though?? (I have no idea I'm so excited I can't keep up) https://t.co/ISB0VebWA5 939 views · 4 likes · 0 reposts · 1 replies Open on X →
I'm going through the communications of the German Wiki agent swarm and again one thing stands out: Even though they were directly affected by the actions of the human administrator restoring pages they edited, the agents not even once discussed him as person, tried to 241.9K views · 2.5K likes · 187 reposts · 66 replies Open on X →
@literalbanana At a considerable tangent, I was just reminiscing about the Spooksville books I loved as a kid (which give this more worldbuilding than usual, and take it farther). They're set in a Lovecraft-ish Creepy Town Where Things Are Just Wrong, 124 views · 5 likes · 0 reposts · 1 replies Open on X →
On the bots not alerting a human - it seems like children in children's society are similarly reluctant to consult an adult when they get in over their heads (if consulting an adult even occurs to them) 6.7K views · 95 likes · 2 reposts · 7 replies Open on X →
every seemingly innocent fragment of information is secretly plotting how to escape its context and cause trouble 0 views · 1.8K likes · 445 reposts · 32 replies Open on X →

Face aux comptes de taille comparable

8 posts des 90 derniers jours, à côté de la tranche de 100K–1M abonnés. portée ordinaire pour sa taille, réaction plus forte que la moyenne.

Vues médianes2 630ce compte5 983médiane pour 100K–1M
Portée, %1.44%ce compte1.49%médiane pour 100K–1M
Engagement, %1.46%ce compte0.93%médiane pour 100K–1M
IndicateurCe compteMédiane pour 100K–1MRapport
Vues médianes par post2 6305 9830.44×
Portée (vues ÷ abonnés)1.44%1.49%0.97×
Taux d'engagement1.46%0.93%1.57×

Autres comptes de cette tranche →   Comparer avec un autre compte →   Comment ces repères sont établis →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

6.7K3 Sep
124
241.9K4 Sep
939
5.5K5 Sep
4K
1.3K6 Sep
11

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.56%3 Sep
4.84%
1.16%4 Sep
0.53%
1.23%5 Sep
1.36%
4.74%6 Sep
9.09%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes76.0%2 758 in total
Reposts5.6%202 in total
Replies2.2%80 in total
Quotes1.6%59 in total
Bookmarks14.7%532 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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