YouTube Comments Scraper

Extract comments from one or many YouTube videos in a simple, scalable way.

This actor is built for creators, marketers, researchers, agencies, and data teams that need structured YouTube comment data without dealing with manual scraping or unstable workflows.

Just provide a list of YouTube video URLs or video IDs, choose how many comments you want per video, and the actor will handle the rest.

It supports:

• multiple videos in one run
• automatic pagination
• retries with exponential backoff
• API key failover
• duplicate protection
• pay-per-event budget protection

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Why use this actor

YouTube comments are one of the best sources for understanding:

• audience sentiment
• customer feedback
• community reactions
• trend signals
• engagement quality
• competitor audience behavior

This actor helps you collect that data in a clean, structured format that is ready for export, analysis, enrichment, or automation.

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What this actor does

For each YouTube video you provide, the actor:

1. extracts the video ID
2. requests comments from the API
3. paginates through additional comment pages
4. retries automatically if the API has a temporary failure
5. fails over to another API key if the main one fails
6. removes duplicates
7. saves structured results to the dataset

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Main features

• Scrape comments from one or many YouTube videos
• Accepts video URLs or raw video IDs
• Supports comment sorting by:
  • newest
  • top
• Handles pagination automatically
• Uses retry + exponential backoff for resilience
• Supports multiple API keys with failover
• Stops safely when the run budget limit is reached
• Returns clean, structured, export-ready data

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Input

This actor uses a simple input structure.

videos

A list of YouTube video URLs or raw video IDs.

Examples:

• https://www.youtube.com/watch?v=1gxf6flnvNA
• https://youtu.be/1gxf6flnvNA
• 1gxf6flnvNA

resultsLimit

Maximum number of unique comments to download per video.

If you provide 3 videos and set resultsLimit = 1000, the actor will try to return up to 1000 unique comments per video.

sortBy

Choose the comment sorting mode:

• newest
• top

rapidApiKeys

A list of RapidAPI keys.

The actor always starts with the first key and only switches to the next one if the current key fails.

requestDelaySec

Delay between pagination requests for the same video.

maxRetries

Maximum retry attempts per provider before failover.

baseBackoffSec

Base delay used for exponential backoff.

minimumResultsRequired

Minimum number of chargeable comments required before the actor starts scraping a video.

requireFullFirstVideo

If enabled, the actor will not start unless the run budget can cover the full requested comment limit for the first video.

timeoutSecs

HTTP timeout for API requests.

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Example input

{
  "videos": [
    "https://www.youtube.com/watch?v=1gxf6flnvNA",
    "1gxf6flnvNA"
  ],
  "resultsLimit": 1000,
  "sortBy": "newest"

}

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Output

Each dataset item represents one YouTube comment.

Output fields

• video_id
• video_url
• sort_by
• commentId
• authorText
• authorChannelId
• authorThumbnail
• textDisplay
• publishedTimeText
• publishDate
• publishedAt
• likesCount
• replyCount
• replyToken
• authorIsChannelOwner
• isVerified
• isArtist
• isCreator

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Example output

{
  "video_id": "1gxf6flnvNA",
  "video_url": "https://www.youtube.com/watch?v=1gxf6flnvNA",
  "sort_by": "newest",
  "commentId": "UgzcQiVfAcJ5WGugXg14AaABAg",
  "authorText": "@odipglance5707",
  "authorChannelId": "UCr8Ld4tMJgQS4K5Oq1oDMtQ",
  "authorThumbnail": "https://yt3.ggpht.com/...",
  "textDisplay": "Who ever get this idea first is a genius!",
  "publishedTimeText": "2 years ago",
  "publishDate": "2024-04-13",
  "publishedAt": "2024-04-13T00:00:00Z",
  "likesCount": "0",
  "replyCount": "0",
  "replyToken": null,
  "authorIsChannelOwner": false,
  "isVerified": false,
  "isArtist": false,
  "isCreator": false
}

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Best use cases

Audience sentiment analysis

Understand how viewers react to a video, topic, product, or creator.

Competitor research

Analyze the comments on competing YouTube channels and videos.

Influencer and creator research

See how audiences respond to creator content and engagement strategies.

Market research

Collect direct audience opinions at scale.

Lead and insight generation

Find repeated questions, pain points, feedback patterns, and audience language.

AI and NLP workflows

Use comment data for classification, clustering, sentiment scoring, moderation analysis, or summarization.

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Reliability and budget protection

This actor is designed to be resilient in real-world scraping conditions.

It includes:

• automatic retries
• exponential backoff
• API key failover
• duplicate protection
• pagination loop protection
• run budget checks before scraping and before pushing data

This helps reduce wasted runs and prevents unnecessary downloads when the available budget is too low.

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Notes

• The actor returns unique comments per video.
• Final results depend on:
  • the requested resultsLimit
  • API stability
  • available pagination
  • the run’s charge limit
• Very active videos may require more requests and more time.

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Built for scalable comment extraction

Whether you are doing brand monitoring, creator research, sentiment analysis, or audience intelligence, this actor gives you a fast and practical way to collect YouTube comments in bulk.