YouTube Comments Scraper - Text, Likes & Authors

Scrape YouTube comments from public videos: point it at watch links, youtu.be links, Shorts links or bare video ids and you get the comments as flat rows with the text, the author handle and channel id, the like and reply counts, the verified badge and the avatar. No API key to request.

Read the like count before you build anything on it. YouTube abbreviates it on the page, so a comment with 315,000 likes arrives as the string "315K". Small numbers come through exact, large ones do not, and the exact figure is not recoverable from the text.

Input	Watch, youtu.be or Shorts links, or bare 11 character video ids
Output	One row per comment: text, author handle and channel id, verified badge, avatar, likes and replies as YouTube shows them, relative date
Ceiling	10,000 comments per run
Account needed	None
Price	$0.40 per 1,000 comments on the Free plan, a little less on paid plans. The free plan's $5 a month covers about 12,500

🔍 What YouTube Comments Scraper does

It reads each video's comment list in YouTube's own default order, which is roughly top comments rather than newest first, and pages through it until the budget runs out.

maxComments is the budget for the whole run, divided evenly across your videos. 500 over five videos is about 100 from each, not 500 from the first. The division rounds down and the remainder is not handed back, so 100 across three videos returns at most 99. Ask for fewer comments than you have videos and each one gets exactly one.

Pass videoUrls and videoIds together if that is what you have. They are merged and deduplicated before anything is fetched.

📋 What data you get from each YouTube comment

What you get	Field
The comment as written	text
The video it sits under	videoId
Who wrote it: the handle as displayed and the stable channel id	author, authorChannelId
Verified tick and avatar	authorIsVerified, authorAvatar
Likes and replies, as YouTube shows them	likeCount, replyCount
When it was posted, as relative text	publishedTime
Whether it is a reply to another comment	isReply
A key to dedupe on	id

▶️ How to scrape YouTube comments

1. Open YouTube Comments Scraper and click Try for free.
2. Paste links into Video URLs, or ids into Video IDs.
3. Set Max comments. Start at 100 while you look at the output.
4. Click Start.
5. Download the dataset as JSON, CSV or Excel, or read it over the Apify API.

Send at least one video. With nothing usable in either field the run fails rather than returning an explanatory row.

💰 How much does it cost to scrape YouTube comments?

$0.40 per 1,000 comments on the Free plan. Paid plans pay a little less: $0.395 on Starter, $0.39 on Scale and $0.385 on Business. On the free plan, the $5 Apify gives you each month covers about 12,500 comments.

You pay per comment row delivered. Diagnostic rows and duplicates dropped inside a run are never billed, so a video with comments switched off delivers no charged rows. maxComments is the ceiling on both the rows and the spend.

📥 What you give it

{
  "videoUrls": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    "https://youtu.be/9bZkp7q19f0"
  ],
  "maxComments": 500
}

Field	Default	What it is
videoUrls	none	Watch links, youtu.be short links and /shorts/ links all parse. The form opens with one example link.
videoIds	none	Or bare 11 character ids, if that is what your pipeline holds.
maxComments	100	Total across every video in the run, 1 to 10,000. This is also your spend cap.
notionConnector, notionParentId	none	Optional. Write each comment into a Notion database as well as the dataset.
proxyConfiguration	none	Optional. Leave it empty unless you have your own servers you want the run to go out through.

📤 What you get back

A real row from a real run, with the avatar link cut short:

{
  "ok": true,
  "type": "comment",
  "id": "EhpVZ3pnZTM0MGRCZ0I3NWhXQm01NEFhQUJBZyAoKAE%3D",
  "videoId": "dQw4w9WgXcQ",
  "text": "can confirm: he never gave us up",
  "publishedTime": "1 year ago",
  "likeCount": "315K",
  "replyCount": "963",
  "isReply": false,
  "author": "@YouTube",
  "authorChannelId": "UCBR8-60-B28hp2BmDPdntcQ",
  "authorIsVerified": true,
  "authorAvatar": "https://yt3.ggpht.com/3s6evpqAiDU9tQR4sC2siJippbH2RWVPnwHgyl4V0th2iuQz0VDQZbUhQBGmsxLYo-..."
}

Field	How to read it
text	Newlines and all.
authorChannelId	Join on this, because handles change.
likeCount, replyCount	Display strings, abbreviated by YouTube: "315K", "963". Not numbers.
publishedTime	Relative text such as "1 year ago". There is no absolute timestamp to read.
isReply	true when the row sits under another comment rather than at the top level.
id	The comment's key from the page. Unique within a video, and stable enough to dedupe on.

🧾 Reading the output

Two kinds of row land in your dataset.

Row	How to spot it	Billed
A comment	ok: true and type: "comment"	yes
A diagnostic	ok: false and an errorCode	no

Filter on ok == true and you have your data. A video whose comment list could not be read gets one uncharged NO_RESULTS row naming the videoId, and the run moves on. Any other errorCode means that video would not answer this run, and re-running usually clears it.

Read a NO_RESULTS row as "the list did not come back", not as "this video has no comments." Comments being switched off is the usual reason, and it is the reason the row text gives, but a request that came back without the list looks the same from here. If a video you know has comments returns NO_RESULTS, run it again on its own before believing it.

A TIME_LIMIT row means the run got close to its time limit and stopped on its own. The comments delivered before that are in the dataset and charged as usual; give the run more time, or ask for fewer comments, to get the rest. A run ends as failed only when the time limit stopped it before any comment came back.

The Overview table shows the comment columns only, so a diagnostic reads as a blank line there. Open the row or download the JSON for the errorCode.

💡 What people use it for

• Reading a launch video's reaction without scrolling for an hour. The upvoted comments come first, which is where the complaints sit as well as the praise.
• Pulling a few hundred comments off videos in your market and seeing which two or three questions keep coming back. That is what your own page should answer.
• Collecting quotes for research, with the handle and channel id attached for attribution.

From a keyword to the questions your market keeps asking, in three runs:

1. Run YouTube Scraper on a keyword in your market and copy the url column.
2. Paste those links into Video URLs here and read down the text column.
3. Paste the same links into the Video URLs or IDs box of YouTube Transcript Scraper to compare what each video says with what its viewers asked.

🚧 What it does not do

• Reply threads are not expanded. Every row carries replyCount, so you know how much conversation sits under a comment, and replies YouTube returns inline are marked isReply: true. It does not open each "view 963 replies" thread. If you need complete reply trees, this is not it.
• No video-level data. Every row is about the comment. The title, view count and description are not in it, so use a video scraper for those.
• Top comments order only. There is no newest-first or sort option, because the page does not offer one without signing in.
• Like and reply counts are abbreviated strings. Sort on them and "1.2K" orders as text.
• No real timestamps. publishedTime is relative to when the run read the page.
• The budget divides evenly, so one video in a long list cannot take more than its share.
• It is not an official YouTube tool. Dami's Studio is independent and is not affiliated with or endorsed by YouTube or Google, or by any other company named on this page.

🧭 Which YouTube scraper do you need?

If you want	Use
Comments under a video	This one
Videos to run this on, by keyword or a channel's newest uploads	YouTube Scraper
A channel's uploads, up to 2,000 per run	YouTube Channel Scraper
What a video says, as text, SRT and VTT	YouTube Transcript Scraper
Shorts from a channel or a keyword, with exact view and like counts	YouTube Shorts Scraper
Comments under a TikTok video	TikTok Comments Scraper
Comments under an Instagram post or reel	Instagram Comments Scraper

❓ Questions people ask

Do I need a YouTube or Google account?

No. Nothing here is signed in.

Is maxComments per video?

No, per run, split evenly across the videos you pass.

Can I get every comment on a big YouTube video?

Up to 10,000 in one run, in YouTube's top-comments order. There is no resume, so a second run starts at the top again.

Why are the like counts text?

Because that is what the page prints. "315K" is YouTube's own rounding, and the exact number is not on the page to read.

Can I filter comments by keyword or date?

Not in the input. Pull the comments and filter text and publishedTime yourself.

Can I call it from code or connect it to an AI assistant?

Yes. The API tab has ready-made code for Python, JavaScript and the command line. For Claude, ChatGPT or another MCP client, connect https://mcp.apify.com/?tools=fetch-actor-details,dami_studio/youtube-comments-scraper. Either way the run happens on your Apify account at the same price.

Is scraping YouTube comments legal?

This reads public comments on public videos. They are personal data, which GDPR and similar laws cover, so have a reason for collecting them and be careful about republishing handles. Apify's write-up on the legality of web scraping is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Include the video link you used and the run ID, and the log is enough for us to see what happened.