YouTube Comments Scraper

Scraper

$2.5/1000

results

Scrape YouTube video comments at scale with per-video caps — structured audience voice for sentiment, FAQ mining, and moderation. $2.50 per 1,000 comments.

Scraping Dino

4.0(4)

Try it out

YouTube Comments Scraper

Scraper

Scrape YouTube video comments at scale with per-video caps — structured audience voice for sentiment, FAQ mining, and moderation. $2.50 per 1,000 comments.

Scraping Dino

4.0(4)

$2.5/1000results

Try it out

Scraping Dino YouTube Comments

Bring comment threads into analytics without copying the YouTube UI.

On Scrapy.io, Scraping Dino YouTube Comments by Scraping Dino is built for scraping youtube workflows — run from the Store, schedule recurring jobs, or POST to scrapingdino.p.scrapy.io from your stack.

What it does

Scrapes comments for one or more video IDs/URLs
Caps with maxResults per video
Returns author, text, likes, and timing fields

Why teams scrape YouTube with Scraping Dino

YouTube is the largest public video catalog — channel stats, upload cadence, comments, and recommendation graphs power creator research, competitive intelligence, and audience insight. A scraping youtube job on Scrapy.io hydrates channel URLs, video IDs, or search queries into structured JSON without maintaining your own headless browser farm.

Scraping Dino YouTube Comments supports batch inputs (channels, video IDs, or keywords) with per-target caps so nightly jobs stay within budget. Export to JSON, CSV, or Excel, or POST the same payload to scrapingdino.p.scrapy.io from your backend.

Scraping Dino YouTube tools chain naturally: resolve channels, list uploads or Shorts, scrape comments on top performers, or expand related videos for graph analysis — all with warehouse-friendly schemas.

What data can Scraping Dino YouTube Comments extract?

This scraping youtube on Scrapy.io exports structured fields including:

Comment ID — Unique identifier
Author — Commenter display name
Text — Comment body
Likes — Like count
Reply count — Number of replies
Published time — Comment timestamp
Video ID — Source video

How to run on Scrapy.io

Open Scraping Dino YouTube Comments on the Scrapy.io Store.
Click Try for free or Run.
Fill in the input form (see Input below) or paste JSON from the example.
Click Start and wait for the run to complete.
Download results from the Output tab, or fetch them via the publisher API.

For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.

Search intent and keywords

Teams discover Scraping Dino YouTube Comments while researching scraping youtube and related terms such as youtube scraper, scrape youtube, youtube scrape, youtube scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.

If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.

Quick start checklist

Use this checklist before your first production run of Scraping Dino YouTube Comments:

Validate inputs — paste a single URL, username, query, or place ID and confirm the Output shape matches your schema
Set caps — tune maxResults, maxReviews, or equivalent limits so a full batch stays within budget
Inspect errors — open the Errors view; fix malformed inputs rather than retrying the entire run blindly
Export once — download JSON and share with stakeholders for sign-off on columns and row volume
Promote to API — copy the same JSON to a POST against scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api or create a scheduled job

Most teams keep a "golden" input file in git for Scraping Dino YouTube Comments so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.

Input

Provide video URLs or 11-character video IDs.

Configure the run in the Scrapy.io input form or pass JSON to the publisher API.

Input JSON example

{
  "videoIds": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "maxResults": 100
}

Field	Type	Required	Description
`videoIds`	string[]	Yes	YouTube video URLs or 11-character video IDs
`maxResults`	integer	No	Maximum comments per video (1–1000)

Output

Results appear in the Scrapy.io run Output tab. Comments and Errors tables.

Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.

JSON example

[
  {
    "type": "comment",
    "videoId": "dQw4w9WgXcQ",
    "commentId": "comment_abc",
    "author": "viewer_1",
    "text": "Great video!",
    "likeCount": 42,
    "publishedTime": "2026-05-10T08:30:00.000Z"
  }
]

Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.

Where teams use the data

Sentiment & VOC

quantify reaction to launches

Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Scraping Dino with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.

FAQ mining

surface repeated questions for help centers

Creator feedback

theme analysis for content teams

Brand safety

flag toxic spikes under campaigns

Why Scraping Dino

Comments exported for NLP and warehouse jobs, with clear caps so costs stay predictable. Prefer Scraping Dino when comment data is a recurring pipeline, not a manual export.

Pipeline patterns with Scraping Dino

Scraping Dino YouTube Comments is rarely the only step in a data workflow. Teams typically:

Pair with YouTube Video Scraper metadata for title and channel context
Run after YouTube Search Scraper to comment-mine trending topics

See Related Scraping Dino tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.

Loading Scraping Dino YouTube Comments data into your warehouse

Most production deployments follow the same shape:

Extract — scheduled Scrapy.io run or API POST with your input JSON
Stage — land raw JSON in S3, GCS, or a staging Postgres schema
Normalize — map Output columns to typed tables (posts, comments, businesses, videos, etc.)
Dedupe — key on stable IDs (postUrl, placeId, videoId, reviewId, …) plus scrape date where history matters
Serve — expose dbt models or API views to BI, CRM enrichment, or alerting

Scraping Dino YouTube Comments separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Scraping Dino tools on those stable keys to build multi-step datasets without re-scraping upstream steps.

Build vs. buy: why use Scraping Dino YouTube Comments on Scrapy.io?

Maintaining Reddit, Maps, or YouTube extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. Scraping Dino YouTube Comments on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.

Scraping Dino listings add warehouse-first documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.

Export formats and delivery

Scraping Dino YouTube Comments runs on Scrapy.io support multiple ways to get data out:

JSON — best for APIs, agents, and document stores; preserves nested fields
CSV — spreadsheet-friendly flat exports for analysts
Excel — formatted downloads for stakeholder review
Publisher API — POST inputs and poll or webhook results into your own pipeline
Webhooks — push finished runs to Slack, Zapier, or custom endpoints

For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.

Scheduling and automation

Run Scraping Dino YouTube Comments once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:

Daily discovery — refresh feeds, search queries, or Maps targets on a cron
Event-driven enrichment — webhook from your CRM when a new URL or place ID appears
API batch jobs — your backend POSTs to scrapingdino.p.scrapy.io on a queue

Scraping Dino tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, maxReviews, or equivalent limits in the input form.

Pricing

$2.50 per 1,000 comments

Publisher API

curl -X POST "https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{
    "videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "maxResults": 200
  }'

Bulk runs via the scraper endpoint:

curl -X POST "https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/scraper" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{
    "videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "maxResults": 200
  }'

Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.

MCP and agent workflows

Scraping Dino YouTube Comments is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.

For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on Scraping Dino YouTube Comments for MCP connection snippets.

Tool	Best for
Scraping Dino YouTube Channel Profiles	Scraping Dino companion tool — overview
Scraping Dino YouTube Channel Shorts	Scraping Dino companion tool — overview
Scraping Dino YouTube Channel Videos	Scraping Dino companion tool — overview

Tips for scaling runs

Cap at 100 comments per video for sentiment screening; raise for research corpora
Batch video IDs from analytics exports
Inspect per-row errors in the Errors output view instead of failing an entire batch
When Maps, Reddit, or YouTube batches repeat the same error, raise Issues on this Scraping Dino listing with your run ID and a sample input

Limitations

Comments disabled on a video yield empty results
Very popular videos need higher maxResults for representative samples

Scraping Dino YouTube Comments collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.

Frequently asked questions

How much does Scraping Dino YouTube Comments cost?

$2.50 per 1,000 comments. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.

Can I integrate Scraping Dino YouTube Comments with other apps?

Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.

Can I use Scraping Dino YouTube Comments with the Scrapy.io API?

Yes. POST to https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.

Can I use Scraping Dino YouTube Comments through an MCP server?

Yes. Configure the Scrapy.io MCP endpoint with your API key to query Scraping Dino YouTube Comments from AI assistants and agent workflows.

Scraping Dino YouTube Comments is not working — what should I do?

Verify inputs (URLs, queries, identifiers) are valid and public
Lower volume caps and retry
Check the run log for per-row errors in the Errors output view
Log the failure in Issues on this Scraping Dino tool page (run ID + place ID, subreddit, or video URL)

Your feedback

Scraping Dino maintains deep Maps, Reddit, and YouTube coverage — star the tool in Reviews if exports are landing in your warehouse and mention which dataset you rely on most.

Similar Tools

View all

YouTube Video Finder

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$0.94

Search YouTube by keyword and return matching videos.

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$5.49

Fetch metadata for one or more YouTube videos.

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Fetch YouTube channel profile metadata and statistics from handles, URLs, or channel IDs.

4.4(5)108

Scraping Dino YouTube Comments

Bring comment threads into analytics without copying the YouTube UI.

What it does

Scrapes comments for one or more video IDs/URLs
Caps with maxResults per video
Returns author, text, likes, and timing fields

Why teams scrape YouTube with Scraping Dino

What data can Scraping Dino YouTube Comments extract?

This scraping youtube on Scrapy.io exports structured fields including:

Comment ID — Unique identifier
Author — Commenter display name
Text — Comment body
Likes — Like count
Reply count — Number of replies
Published time — Comment timestamp
Video ID — Source video

How to run on Scrapy.io

Open Scraping Dino YouTube Comments on the Scrapy.io Store.
Click Try for free or Run.
Fill in the input form (see Input below) or paste JSON from the example.
Click Start and wait for the run to complete.
Download results from the Output tab, or fetch them via the publisher API.

For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.

Search intent and keywords

If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.

Quick start checklist

Use this checklist before your first production run of Scraping Dino YouTube Comments:

Validate inputs — paste a single URL, username, query, or place ID and confirm the Output shape matches your schema
Set caps — tune maxResults, maxReviews, or equivalent limits so a full batch stays within budget
Inspect errors — open the Errors view; fix malformed inputs rather than retrying the entire run blindly
Export once — download JSON and share with stakeholders for sign-off on columns and row volume
Promote to API — copy the same JSON to a POST against scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api or create a scheduled job

Input

Provide video URLs or 11-character video IDs.

Configure the run in the Scrapy.io input form or pass JSON to the publisher API.

Input JSON example

{
  "videoIds": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "maxResults": 100
}

Field	Type	Required	Description
`videoIds`	string[]	Yes	YouTube video URLs or 11-character video IDs
`maxResults`	integer	No	Maximum comments per video (1–1000)

Output

Results appear in the Scrapy.io run Output tab. Comments and Errors tables.

Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.

JSON example

[
  {
    "type": "comment",
    "videoId": "dQw4w9WgXcQ",
    "commentId": "comment_abc",
    "author": "viewer_1",
    "text": "Great video!",
    "likeCount": 42,
    "publishedTime": "2026-05-10T08:30:00.000Z"
  }
]

Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.

Where teams use the data

Sentiment & VOC

quantify reaction to launches

FAQ mining

surface repeated questions for help centers

Creator feedback

theme analysis for content teams

Brand safety

flag toxic spikes under campaigns

Why Scraping Dino

Comments exported for NLP and warehouse jobs, with clear caps so costs stay predictable. Prefer Scraping Dino when comment data is a recurring pipeline, not a manual export.

Pipeline patterns with Scraping Dino

Scraping Dino YouTube Comments is rarely the only step in a data workflow. Teams typically:

Pair with YouTube Video Scraper metadata for title and channel context
Run after YouTube Search Scraper to comment-mine trending topics

See Related Scraping Dino tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.

Loading Scraping Dino YouTube Comments data into your warehouse

Most production deployments follow the same shape:

Extract — scheduled Scrapy.io run or API POST with your input JSON
Stage — land raw JSON in S3, GCS, or a staging Postgres schema
Normalize — map Output columns to typed tables (posts, comments, businesses, videos, etc.)
Dedupe — key on stable IDs (postUrl, placeId, videoId, reviewId, …) plus scrape date where history matters
Serve — expose dbt models or API views to BI, CRM enrichment, or alerting

Build vs. buy: why use Scraping Dino YouTube Comments on Scrapy.io?

Export formats and delivery

Scraping Dino YouTube Comments runs on Scrapy.io support multiple ways to get data out:

JSON — best for APIs, agents, and document stores; preserves nested fields
CSV — spreadsheet-friendly flat exports for analysts
Excel — formatted downloads for stakeholder review
Publisher API — POST inputs and poll or webhook results into your own pipeline
Webhooks — push finished runs to Slack, Zapier, or custom endpoints

For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.

Scheduling and automation

Run Scraping Dino YouTube Comments once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:

Daily discovery — refresh feeds, search queries, or Maps targets on a cron
Event-driven enrichment — webhook from your CRM when a new URL or place ID appears
API batch jobs — your backend POSTs to scrapingdino.p.scrapy.io on a queue

Scraping Dino tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, maxReviews, or equivalent limits in the input form.

Pricing

$2.50 per 1,000 comments

Publisher API

curl -X POST "https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{
    "videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "maxResults": 200
  }'

Bulk runs via the scraper endpoint:

curl -X POST "https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/scraper" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{
    "videoIds": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
    "maxResults": 200
  }'

Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.

MCP and agent workflows

Tool	Best for
Scraping Dino YouTube Channel Profiles	Scraping Dino companion tool — overview
Scraping Dino YouTube Channel Shorts	Scraping Dino companion tool — overview
Scraping Dino YouTube Channel Videos	Scraping Dino companion tool — overview

Tips for scaling runs

Cap at 100 comments per video for sentiment screening; raise for research corpora
Batch video IDs from analytics exports
Inspect per-row errors in the Errors output view instead of failing an entire batch
When Maps, Reddit, or YouTube batches repeat the same error, raise Issues on this Scraping Dino listing with your run ID and a sample input

Limitations

Comments disabled on a video yield empty results
Very popular videos need higher maxResults for representative samples

Frequently asked questions

How much does Scraping Dino YouTube Comments cost?

$2.50 per 1,000 comments. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.

Can I integrate Scraping Dino YouTube Comments with other apps?

Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.

Can I use Scraping Dino YouTube Comments with the Scrapy.io API?

Yes. POST to https://scrapingdino.p.scrapy.io/youtube-comments-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.

Can I use Scraping Dino YouTube Comments through an MCP server?

Yes. Configure the Scrapy.io MCP endpoint with your API key to query Scraping Dino YouTube Comments from AI assistants and agent workflows.

Scraping Dino YouTube Comments is not working — what should I do?

Verify inputs (URLs, queries, identifiers) are valid and public
Lower volume caps and retry
Check the run log for per-row errors in the Errors output view
Log the failure in Issues on this Scraping Dino tool page (run ID + place ID, subreddit, or video URL)

Your feedback

Scraping Dino maintains deep Maps, Reddit, and YouTube coverage — star the tool in Reviews if exports are landing in your warehouse and mention which dataset you rely on most.

Similar Tools

View all

YouTube Video Finder

ScraperAPI

$0.94

Search YouTube by keyword and return matching videos.

5.0(4)131

YouTube Video Data Extractor

ScraperAPI

$5.49

Fetch metadata for one or more YouTube videos.

4.3(3)121

YouTube Channel Insights Scraper

ScraperAPI

$5.41

Fetch YouTube channel profile metadata and statistics from handles, URLs, or channel IDs.

4.4(5)108

YouTube Comments Scraper

YouTube Comments Scraper

Scraping Dino YouTube Comments

What it does

Why teams scrape YouTube with Scraping Dino

What data can Scraping Dino YouTube Comments extract?

How to run on Scrapy.io

Search intent and keywords

Quick start checklist

Input

Input JSON example

Output

JSON example

Where teams use the data

Sentiment & VOC

FAQ mining

Creator feedback

Brand safety

Why Scraping Dino

Pipeline patterns with Scraping Dino

Loading Scraping Dino YouTube Comments data into your warehouse

Build vs. buy: why use Scraping Dino YouTube Comments on Scrapy.io?

Export formats and delivery

Scheduling and automation

Pricing

Publisher API

MCP and agent workflows

Related Scraping Dino tools on Scrapy.io

Tips for scaling runs

Limitations

Frequently asked questions

How much does Scraping Dino YouTube Comments cost?

Can I integrate Scraping Dino YouTube Comments with other apps?

Can I use Scraping Dino YouTube Comments with the Scrapy.io API?

Can I use Scraping Dino YouTube Comments through an MCP server?

Scraping Dino YouTube Comments is not working — what should I do?

Your feedback

Similar Tools

YouTube Video Finder

YouTube Video Data Extractor

YouTube Channel Insights Scraper

Scraping Dino YouTube Comments

What it does

Why teams scrape YouTube with Scraping Dino

What data can Scraping Dino YouTube Comments extract?

How to run on Scrapy.io

Search intent and keywords

Quick start checklist

Input

Input JSON example

Output

JSON example

Where teams use the data

Sentiment & VOC

FAQ mining

Creator feedback

Brand safety

Why Scraping Dino

Pipeline patterns with Scraping Dino

Loading Scraping Dino YouTube Comments data into your warehouse

Build vs. buy: why use Scraping Dino YouTube Comments on Scrapy.io?

Export formats and delivery

Scheduling and automation

Pricing

Publisher API

MCP and agent workflows

Related Scraping Dino tools on Scrapy.io

Tips for scaling runs

Limitations

Frequently asked questions

How much does Scraping Dino YouTube Comments cost?

Can I integrate Scraping Dino YouTube Comments with other apps?

Can I use Scraping Dino YouTube Comments with the Scrapy.io API?

Can I use Scraping Dino YouTube Comments through an MCP server?

Scraping Dino YouTube Comments is not working — what should I do?

Your feedback

Similar Tools

YouTube Video Finder

YouTube Video Data Extractor

YouTube Channel Insights Scraper