YouTube Comments Scraper: Export Every Comment to JSON

Hosted youtube comments scraper that returns the top-level comments from any public YouTube video as structured JSON, author, text, like count, reply count, pin/heart status. Run it from the Apify Store with one click, or call it from your own service via the Apify API. Pay per comment, not per month.

If you've been searching for a youtube comment scraper chrome extension that doesn't require running Chrome yourself, a youtube comment scraper python github repo that's actually maintained, or a way to do how to scrape youtube comments at scale without dealing with the YouTube Data API's strict quota, this Actor is the hosted alternative.

What you get

• Structured comment records, comment ID, author handle, channel ID, verified flag, full text, like count, reply count, pinned/hearted flags.
• Up to 2,000 top-level comments per run, paginated through YouTube's internal /youtubei/v1/next endpoint with proper continuation-token handling.
• No YouTube Data API quota required, the Actor uses YouTube's own internal web API (the same one the YouTube web client calls for lazy-loading the comments panel), so you don't burn any of your 10,000 daily quota units.
• Works for any public video, no auth, no key, no cookies needed.
• Pay only for what you scrape, pricing scales per comment returned. No subscription minimum.

Why use a youtube comments scraper

YouTube comments are a goldmine for product research, sentiment analysis, brand monitoring, and content marketing input. But the official YouTube Data API has tight quotas (10,000 units/day, with commentThreads.list costing 1 unit per call returning up to 100 comments) and silently skips comments on many videos for "spam" reasons. For any serious analysis at scale, you need an alternative.

That's why hundreds of developers have built youtube comment scraper chrome extension plugins, GitHub Python scrapers, and Outscraper-style API services, all trying to solve the same gap. This Actor is the hosted Apify version: maintained as YouTube ships updates, billed per comment, no infrastructure to operate.

Input

Field	Type	Default	Description
video	string	required	YouTube video URL (watch?v=…, youtu.be/…, or /shorts/…) or 11-character video ID.
max_comments	integer	100	Top-level comments to collect (1–2,000). Replies are not expanded in this Actor.

Output

Every run pushes results to the Apify dataset as JSON records, one per top-level comment:

{
  "comment_id": "Ugzge340dBgB75hWBm54AaABAg",
  "author": "@YouTube",
  "author_channel_id": "UCBR8-60-B28hp2BmDPdntcQ",
  "author_is_verified": true,
  "text": "can confirm: he never gave us up",
  "published_text": "1 year ago",
  "like_count": "233K",
  "reply_count": 961,
  "is_pinned": false,
  "is_hearted": false,
  "video_id": "dQw4w9WgXcQ",
  "video_url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
  "fetched_in_seconds": 3.4
}

You can:

• Download the dataset as JSON, JSONL, CSV, or Excel from the Apify console
• Stream results via the Apify API for use in your own application
• Pipe results to webhooks, S3, BigQuery, or any of Apify's 30+ integrations
• Diff today's run against yesterday's to track new comments and engagement growth

Use cases

Product feedback mining

For tutorial videos covering your product, scrape comments to surface real user questions and friction points. Cluster by topic and you have an unfiltered Voice-of-Customer feed, directly usable as roadmap input or support-content seed.

Influencer marketing due diligence

Before sponsoring an influencer, scrape comments on their last 10 videos. Authentic engagement looks like 1–3% comment rate with varied, specific text; bot-inflated channels show comment counts that don't match the engagement vocabulary. The data tells you fast which channels are real.

Sentiment analysis and brand monitoring

For any video mentioning your brand or competitors, pull the comments and run sentiment analysis. Comment sentiment lags review-site sentiment by weeks but leads social-media sentiment by days, a useful middle signal.

Content marketing input

What questions do real viewers ask in the comments of top-ranking videos in your niche? Scrape the top 5 videos for each target keyword, cluster the questions, and you have a content brief grounded in actual audience demand.

How it compares

Other ways to pull YouTube comments include another Apify actor, an API service like Outscraper, and open-source scripts on GitHub. Here is how this Actor lines up.

	This Actor	streamers/youtube-comments-scraper (Apify)	Outscraper	bellingcat/youtube-comment-scraper (open source)
Hosted, no Chrome or servers to run	Yes	Yes	Yes	No, you run it yourself
No YouTube Data API key or quota	Yes, uses InnerTube	Yes	Yes	Yes
Structured JSON output	Yes	Yes	Yes	Yes, in your own code
Signup needed beyond the platform	No, run from Apify	No, run from Apify	Outscraper account and API key	No, but self-hosted
Billing	Pay per comment, no subscription	Pay per result	Subscription or credits	Free, self-run

FAQ

Is this youtube comments scraper free?

The Actor itself is hosted on Apify with pay-per-comment pricing, you only pay for the comments you actually receive. There's no monthly subscription. A typical 100-comment run costs a fraction of a dollar.

How does this compare to a youtube comment scraper chrome extension?

Chrome extensions require running Chrome yourself, manual page-by-page operation, and break when YouTube ships UI updates. This Actor runs server-side against YouTube's internal API, returns 100–2,000 comments per run automatically, and is maintained as YouTube evolves.

Is there a youtube comment scraper python github repo I could use instead?

Plenty exist, but most rely on the YouTube Data API (subject to 10k-units/day quota) or scrape the page HTML (breaks every few months when YouTube ships UI updates). This Actor uses the InnerTube API directly and is hosted on Apify infrastructure that's monitored and patched as YouTube evolves.

How to scrape youtube comments without burning my YouTube Data API quota?

That's exactly what this Actor solves. It calls YouTube's internal /youtubei/v1/next endpoint (the same one the YouTube web client uses), no API key, no quota cost. Your 10,000 daily Data API units stay untouched.

What about replies to comments?

This Actor returns top-level comments and the per-comment reply count. Reply expansion (the actual reply text) is not included in the current version, the reply count tells you how active the thread is, but the full reply tree would require a separate Actor pass.

Why is the like_count a string like "1.2K" instead of a number?

That's exactly what YouTube's InnerTube API returns, the localized abbreviated format ("1.2K", "233K", "1.4M") YouTube shows on the page. It's trivial to parse downstream if you need a numeric value, but the Actor returns the raw upstream format unchanged so you can verify it matches what you'd see in a browser.

What happens for videos with comments disabled or members-only?

The Actor returns a structured no_comments error in the run's errors field. This commonly happens with age-restricted content, channels that disable comments, kids-content videos, and live-chat-only streams.

Can I run this on a schedule?

Yes, Apify has built-in scheduling. Most teams schedule daily runs per tracked video to capture new comments as they're posted, then diff against the previous run for incremental analysis.

Pricing

This YouTube comments scraper uses Apify's pay-per-event pricing, every successful comment row costs a small fixed amount, so your bill scales linearly with usage. There's no monthly subscription. See the Apify Store page for the current per-comment price; expect typical workloads (100–500 comments per video) to cost a few cents per run.