Go to example tasks
Sentiment-scored YouTube comments
Ready-to-run example: every comment scored for sentiment, keywords and question intent, plus a summary row with the split.
YouTube Comment Sentiment Analysis Tool - Score at Scalevonsensey/youtube-comment-sentiment-analysis-tool
Row
Comment
Author
Likes
+25 fieldsTextNumberBooleanListObject
Input
YouTube videos, channels, playlists or search phrases:https://www.youtube.com/watch?v=dQw4w9WgXcQ
Add sentiment, keywords and question detection:true
Add a run summary row:true
Output fields
Row
Comment
Author
Likes
Likes approx.
Replies
Is reply
Thread
Parent comment
Published
Published (approx. ISO)
By creator
Verified
Hearted by creator
Author channel
Sentiment
Sentiment score
Toxicity signal
Is question
Keywords
Writing system
Timestamps cited
Video
Video URL
Channel
Comment id
Video id
Sorted by
Scraped at
Sign up on Apify01
Create your Apify account to access the YouTube Comment Sentiment Analysis Tool - Score at Scale.
Start the run02
The Actor will start running based on the input automatically.
Receive the output03
Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.
Integrate into your workflow04
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.
