Question 1

How do I analyze comment sentiment?

Accepted Answer

Export comments with NoteLM, then use sentiment analysis tools (MonkeyLearn, VADER, or ChatGPT) to classify positive, negative, and neutral comments.

Question 2

What can sentiment analysis tell me?

Accepted Answer

Overall reception, controversial sections, audience concerns, feature requests, and emotional responses to your content.

Question 3

Are there free sentiment analysis tools?

Accepted Answer

Yes! VADER (Python library) is free and effective. ChatGPT can analyze sentiment in batches. Google Sheets add-ons also work.

Question 4

How do I identify negative feedback patterns?

Accepted Answer

Filter negative comments, look for repeated themes. Common issues often appear in multiple comments using similar language.

Question 5

Can I track sentiment over time?

Accepted Answer

Yes! Analyze comments from videos posted at different times to see how audience sentiment evolves.

Question 6

What about non-English comments?

Accepted Answer

Many sentiment tools support multiple languages. For best results, analyze each language separately.

Question 7

How accurate is automated sentiment analysis?

Accepted Answer

About 70-85% accuracy for clear sentiments. Sarcasm and context-dependent comments may be misclassified.

Question 8

Should I respond based on sentiment analysis?

Accepted Answer

Focus on addressing negative trends and thanking positive feedback. Don't obsess over individual negative comments.

YouTube Comment Sentiment Analysis FAQ

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