Free example - how coordinated comments look in data

Created by

Mentat Logic

Actor

Fake Comment Detector — coordination audit for comment exports

A 22-comment sample with planted traps: a machine-regular burst the audit must flag, and a single-comment account it must refuse to judge. Evidence attached.

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Fake Comment Detector — coordination audit for comment exportsmentat-logic/mentat-authenticity-audit

Item type

VERDICT

Why

Account

+10 fields

Input

Comment rows to audit

id:c01+21

profileId:90001+21

profileName:Dana R.+21

date:2026-07-20T14:00:00Z+21

text:Absolutely love this, best decision I ever made!+21

Output fields

Item type

VERDICT

Why

Account

Level

Comments

Signals (with evidence)

Bursts found

Unique comments

Duplicates removed

Accounts seen

Pct comments from flagged accounts

Report url

How it works

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Start the "Free example - how coordinated comments look in data" task

The Fake Comment Detector — coordination audit for comment exports Actor will start running based on the input automatically. You can also change all the input fields, like comment rows to audit, to match your specific use case.

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Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as item type, VERDICT, why, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Free example - how coordinated comments look in data" task via API.