TWITTER_POST

FakePsyho argues that most AI reply-bot spam can be detected without analyzing…

2026-03-31 · 16:20 UTC ·FakePsyho ·1 min read

Brief

FakePsyho argues that most AI reply-bot spam can be detected without analyzing tweet text at all. Their Firefox extension relies on a simple temporal threshold over the last 200 tweets, and they claim early testing over a few days showed strong precision: 86% recall on manually labeled suspicious accounts with no hits on a 50-account highly active human control group.

Source evidence

title: @FakePsyho: I got tired of engagement-farming AI reply bots, and a few hours later I had a f...
author: FakePsyho
contenttype: twitterpost
published: 2026-03-31T16:20:01+00:00
source_url: https://x.com/FakePsyho/status/2039014863993786749

word_count: 188

Tweet by @FakePsyho

I got tired of engagement-farming AI reply bots, and a few hours later I had a firefox extension that correctly tags (and hides/collapses if enabled) about 90% of them. Turns out you can detect most of these accounts just by analyzing their posting patterns. Take their last 200 tweets and find the maximum number of reply tweets within any 5-minute window. If it's 4 or higher, it's an automated reply account. I manually tagged 100 suspicious accounts and 50 terminally online accounts. This single if matched 86/100 of sus accounts and none of the terminally online ones. I've been running this for a few days now and I'm still surprised by the accuracy. I'm pretty sure you can detect almost all of this AI slop without even looking at the content of tweets. I manually checked "false positives" I got and all of them were either: (a) accounts spamming gifs/single words/emoji replies, which is more or less the same behavior just without AI (b) accounts that used AI replies in the past. tl;dr: fixing majority of the current slop apocalypse requires a 0.1x engineer and a minimal effort

Posted: 2026-03-31T16:20:01.000Z
Engagement: 258 likes, 12 retweets, 40 replies