Question 1

How do I identify spam in exported comments?

Accepted Answer

Look for: repeated text, excessive links, promotional language, unrelated content, and comments from suspicious accounts.

Question 2

Can I filter spam during export?

Accepted Answer

NoteLM exports all comments. Filter spam afterwards using spreadsheet functions or text analysis tools.

Question 3

What patterns indicate spam comments?

Accepted Answer

URLs (especially shortened), "check out my channel", cryptocurrency mentions, excessive emojis, and generic praise from new accounts.

Question 4

How do I filter spam in Excel/Sheets?

Accepted Answer

Use FILTER with SEARCH to exclude comments containing spam keywords. Create a spam word list and filter against it.

Question 5

Should I remove all links as spam?

Accepted Answer

Not necessarily. Legitimate commenters share relevant links. Focus on promotional patterns rather than all links.

Question 6

What about bot comments?

Accepted Answer

Bot comments often have: generic text, posted within seconds of upload, similar usernames, and repetitive phrasing across videos.

Question 7

Can AI help filter spam?

Accepted Answer

Yes! ChatGPT can classify comments as spam/not-spam. Train a simple model with examples for batch processing.

Question 8

How much spam is typical?

Accepted Answer

Popular videos may have 5-15% spam. Newer/smaller channels see less. Music and crypto topics attract more spam.

Filter Spam from YouTube Comments FAQ

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