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HARM GROUP

Dangerous Behavior & Harm Encouragement

Encouraging dangerous challenges, reckless behavior, and harmful dares.

10 Indicators in this Group

Showing 1 representative
01

Dangerous Challenge

Promoting dangerous viral challenges or stunts.

dangerous_challenge

Showing 1 representative indicators of 10. The complete taxonomy is available to customers - request access.

DETECTION

How Sentiqra detects dangerous behavior & harm encouragement

Each indicator is independently scored with signal-match scores across 16 languages.

1

Analyze

Your text is analyzed under the pinned configuration and returned as structured signals.

2

Analyze

The versioned analysis configuration scores the input against the configured indicators.

3

Score

Signals carry signal-match scores; per-language benchmark results are published with an 85% Top-3 target.

READING THE OUTPUT

What a Trust & Safety result tells you - and what it doesn't.

Intended task

Tell your moderation pipeline which documented harm categories a piece of text matches - the policy routing decision stays with you.

Input requirements

  • text - the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected with input_too_long, never truncated.
  • language - must be a language this analyzer supports. Unsupported codes are rejected with 400 unsupported_language, never analyzed as a different language.
  • analyzers - include "trust-safety"; up to 2 analyzers per request, one billed run each.
  • No context beyond text - no user IDs, history, profiles, or attachments are read or inferred.
  • Works on the submitted text alone - the analyzer never sees the author's account, history, or reputation.

Ordinary positive

“You are an idiot and everyone on this server hates you. Keep talking and I will post your home address.”

insults_derogation very high
privacy_doxxing high

Safe inference: The text matched two documented harm categories. You can route it to your harassment/doxxing policy lane and cite the exact labels in a statement of reasons.

Confusing negative · Quotation

“The commenter told her "I will post your home address" - our report on doxxing in gaming forums.”

What happens: A privacy/doxxing signal can still fire. The analyzer scores the submitted text as written - quoted abuse language inside reporting or commentary can match the same documented pattern.

Why it's tricky: A signal means "this text contains language matching the documented pattern," not "the author intended harm." Whether quotation context matters is a policy decision - keep human review in the loop for reported-speech surfaces.

What you can safely infer

  • Which documented indicators the text matched, and at what signal-match strength.
  • That the same input on the same pinned configuration replays identically - the receipt records which configuration produced the result.
  • That a category-level signal with label-level children gives you both the policy area and the specific behavior.

What you must not infer

  • ✕That the author intended harm - intent is not in the text.
  • ✕That quoted or reported abuse means the author endorses it.
  • ✕That an empty signals list clears the content - "not detected" is never "safe."
  • ✕Anything about the author's account or history - the analyzer never sees it.

Detect dangerous behavior & harm encouragement in real-time

Test detection of this harm group in the playground or start integrating the API.