Capture repeated comment rows and replies
Extract usernames, comment bodies, reply structures, and visible engagement fields from repeated discussion layouts.
YouTube Comments Scraper
Extract YouTube comments and replies into structured datasets
DataLens is a good fit when you need a YouTube comments scraper for research, moderation review, creator ops, or feedback analysis. Capture visible comments and reply threads in the browser, then export the structured result in the format your team needs.
Use this page as a starting point for the full workflow: collect the source, clean the table, analyze the patterns, and keep the exportable file together.
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AI scraping workbench
Collect, clean, and deliver without rebuilding the workflow.
DataLens keeps the messy browser step, the structured table, and the exportable files together so analysts, operators, and growth teams can move from live pages to decisions faster.
Collect
Capture live page evidence
Open the source in Chrome and let DataLens detect repeated rows, links, images, comments, or listings on the page you are already viewing.
Clean
Shape messy fields into a table
Use the AI scraping workbench to normalize labels, preserve source context, and keep raw rows beside the cleaned dataset for review.
Deliver
Export files people can use
Send CSV, Excel, JSON, or a research report to the team without stitching together screenshots, scripts, and disconnected spreadsheets.
Useful for research and moderation review
Export structured discussion data for sentiment review, feedback clustering, creator ops, or community analysis outside the browser.
Choose the export format that fits your workflow
Use Excel or CSV for spreadsheet review, or JSON when your team needs a more structured payload for downstream systems.
Real-world use cases
Review audience feedback and recurring themes across visible YouTube comment sections.
Capture creator-community discussion data for research, moderation, or product analysis.
Export structured comment rows that are easier to filter and analyze than raw page HTML.
How it works
- 1
Open the YouTube video page or comment view you want to analyze.
- 2
Use DataLens to detect repeated comment rows and visible reply structures.
- 3
Review the extracted discussion dataset and export it to Excel, CSV, or JSON.
Frequently asked questions
Use these questions to decide how a live website becomes an AI scraping workflow.
Can a YouTube comments scraper capture replies?
Yes. DataLens is designed to identify repeated comment layouts and visible reply structures so they can be organized into a structured export.
What can I do with exported YouTube comment data?
Teams use it for audience research, feedback review, moderation analysis, sentiment work, and any workflow that benefits from structured comments in Excel, CSV, or JSON.
Is JSON better than CSV for comment exports?
JSON is often the better fit when reply structure matters, while CSV is useful for faster spreadsheet-style analysis of flattened comment records.
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