youtube-comments-api-skill

To extract YouTube comments and video data via API, provide search keywords, comment limits, and scroll counts to the BrowserAct API template. It returns structured datasets containing video metadata, commenter details, and comment texts for analysis.

Yes, you can limit the comments extracted per YouTube video by setting the Comments_limit parameter. You can also adjust the Scroll_count parameter to control how deeply the API loads discussion threads before extraction.

Yes, a BrowserAct API key is required to scrape YouTube video metadata. The extraction script runs in a Python runtime environment and uses the requests dependency to authenticate and fetch structured video titles, URLs, views, and comments.

For sentiment analysis and market research, the extracted YouTube data includes video metadata like titles, URLs, publication times, view counts, along with comment text and commenter details like names and profile URLs.

The scroll count determines how many times the API scrolls down the YouTube page to load additional discussion threads. Increasing the Scroll_count parameter allows the extraction of deeper and older comments associated with the target videos.

Automating audience insight collection from YouTube is best achieved by running the Python extraction script with targeted keywords. The BrowserAct API automatically retrieves and structures video data and comments, providing ready-to-use datasets for competitive monitoring.