⚠ DEMO — SYNTHETIC DATA. Every comment, channel name, count, and video title on this page is an invented example showing the report format. This is not a scan of a real channel. A real scan report follows this exact structure, filled with the channel’s actual public comments.

Comment Health Scan — Demo

Channel: Example Creator (demo channel)  ·  Scope: public comments on the 10 most recent videos  ·  Access: read-only, public comments via the official YouTube Data API. Comments held in YouTube’s review queue are not visible to this scan.

1,240
public comments reviewed (demo)
87
flagged as likely scam/spam (7.0%)
61 high-confidence · 26 suspicious — human review
HIGH
overall channel risk level
Low <1% · Medium 1–3% · High 3–10% · Severe >10% flagged
4 of 10
videos with at least one impersonator

Flagged comments by scam type

Filter the synthetic examples below. Category totals are the demo report’s counts.

Per-video breakdown (demo)

Video (demo titles)CommentsFlaggedRisk
“My honest review after 30 days”21419High
“Beginner mistakes I see every week”18716High
“Live Q&A — your questions answered”17614Medium
“The tool I can’t work without”15211Medium
“What I wish I knew at 1,000 subs”1319Medium
5 remaining videos combined38018Medium

Pattern note (demo): 68% of flagged comments were posted within the first 2 hours after upload — scam accounts monitor new uploads. Checking comments early, or having cleanup run automatically, removes them before most viewers see them.

What this report recommends (demo)

  1. Remove the 61 high-confidence items and block the 9 repeat-offender accounts.
  2. Add blocked words in YouTube Studio: the messenger handles and crypto phrases that appear repeatedly.
  3. Pin a safety comment on the two most-targeted videos: you never contact winners by WhatsApp/Telegram and never promote investments.
  4. Re-scan after your next upload — one scan is a snapshot; the pattern over time shows whether it’s getting better or worse.

Method & limits

This scan reads published public comments only, via the official YouTube Data API. It cannot see comments YouTube is holding for review, deleted comments, or private data of any kind.

Classification is pattern-based (impersonation signals, known lure phrases, off-platform handles, giveaway/crypto patterns). Borderline items are marked “suspicious — human review” rather than asserted as scams.

Percentages describe this channel’s scanned comments, not YouTube overall. (For context, an academic study of 45,322 videos found 31.73% had scam-bot comments — IMC paper.) This report deletes nothing and changes nothing on your channel.

End of demo. All comments, counts, and titles above are synthetic examples.

CleanComments for YouTube (working name) — early validation project by an independent developer.