YouTube comments for sentiment analysis
Collect comments from a long talk to measure audience reaction or feed an LLM for sentiment and topic analysis. This example reads 50 top comments on Andrej Karpathy's "Intro to Large Language Models".
Input
Output fields
Sign up on Apify or log in
The YouTube Video & Shorts Comments Scraper with Replies Actor is ready to run with the inputs already set for "YouTube comments for sentiment analysis". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "YouTube comments for sentiment analysis" task
The YouTube Video & Shorts Comments Scraper with Replies Actor will start running based on the input automatically. You can also change all the input fields, like youtube videos and max comments per video, to match your specific use case.
Receive the "YouTube comments for sentiment analysis" output
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 video, comment, author, 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 "YouTube comments for sentiment analysis" task via API.
