YouTube Comment Extractor

Extract YouTube video comments into structured, analysis-ready datasets. This Apify actor collects top-level comments, author details, timestamps, like counts, and threaded replies — delivering each comment as a structured dataset item ready for sentiment analysis, audience research, and content strategy workflows.

It is designed for teams that need to understand audience reactions, track engagement trends, compare competitor content, or build dependable research datasets from YouTube comments without manually scrolling through every video.

Why use this actor?

• Cost-conscious extraction — submit only the videos you care about instead of paying for channel-wide crawling.
• Batch-friendly performance — process multiple video URLs in one run, with execution designed to maintain useful throughput as the workload changes.
• Rich comment signals — collect author names, comment text, publication timestamps, like counts, and reply threads in one record.
• Consistent dataset output — every comment keeps its source video URL and follows the same predictable structure.
• Apify-native workflow — schedule runs, monitor progress, and export the resulting dataset in the formats your downstream workflow already uses.

What you can collect

Each comment record may include the following publicly visible information:

Category	Fields
Comment identity	Comment text, publication timestamp, like count
Author details	Author display name, author channel URL
Source context	Original video URL
Reply threads	Nested replies with the same structure as top-level comments

The actor keeps the source video URL with every record, making it easy to trace a finding back to the originating video.

Input

Provide one or more YouTube video URLs in startUrls. The field is required and accepts Apify request-list objects.

Field	Type	Required	Description
startUrls	Array of objects	Yes	Video URLs to extract comments from. Each object uses the form { "url": "https://www.youtube.com/watch?v=..." }.
maxComments	Integer	No	Maximum number of top-level comments per video (default: 100).
includeReplies	Boolean	No	Whether to include reply threads (default: true).

Example input

{
  "startUrls": [
    { "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ" }
  ],
  "maxComments": 100,
  "includeReplies": true
}

Output

The actor pushes one dataset item for each extracted comment. A representative result looks like this:

{
  "videoUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
  "commentId": "UgzDE2...",
  "authorName": "Example User",
  "authorChannelUrl": "https://www.youtube.com/channel/UC...",
  "text": "This is a sample comment.",
  "publishedAt": "2024-01-15T10:30:00Z",
  "likeCount": 42,
  "replyCount": 3,
  "replies": [
    {
      "authorName": "Reply User",
      "text": "I agree!",
      "publishedAt": "2024-01-15T11:00:00Z",
      "likeCount": 5
    }
  ]
}

Built for practical workflows

• Audience research — understand viewer sentiment, common questions, and engagement patterns.
• Content strategy — identify what resonates with audiences by analyzing comment themes across videos.
• Competitive analysis — track engagement and sentiment on competitor content over time.
• Brand monitoring — collect feedback and reactions to your own video content at scale.
• Research operations — send the dataset to spreadsheets, warehouses, NLP pipelines, or internal dashboards.

How to run

1. Open the actor in Apify.
2. Add one or more YouTube video URLs to startUrls.
3. Optionally adjust maxComments and includeReplies.
4. Start the run.
5. Review the dataset or export it as JSON, CSV, Excel, or another supported format.

Important limitations

• The actor extracts publicly visible comments; it does not access private or unlisted video comments without appropriate access.
• YouTube may rate-limit or throttle comment loading for videos with very large comment sections.
• Results depend on the comments publicly displayed on each video at run time; deleted or moderated comments are not available.
• Comment threading depth is limited to one level of replies (reply-to-reply chains are flattened).
• Comment and author fields can change as YouTube updates its page structure.

Use the collected information in accordance with YouTube's terms of service, applicable privacy requirements, and your organization's data-use policies.