YouTube Comments Scraper

by akash9078

Scrape YouTube comments for sentiment analysis and research. Extract comment text, authors, timestamps, likes, and full reply threads into a structured dataset.

118 runs

8 users

Try This Actor

Opens on Apify.com

About YouTube Comments Scraper

Need to know what people are really saying about a video? This YouTube Comments Scraper pulls all the data you see on-screen into a structured dataset you can actually work with. I use it to grab every comment, the username of the person who posted it, the exact timestamp, and how many likes it got. It also captures full reply threads, so you get the complete conversation, not just the top-level comments. This is the kind of data that’s gold for a few key things. If you're running any kind of sentiment analysis, you've got a clean feed of raw public opinion. For competitor research, you can see exactly which points in a rival's video sparked the most discussion or pushback. And if you're planning your own content, scanning the comments on similar successful videos shows you what questions viewers have or what they felt was missing. You get the data in a format (like JSON or CSV) that's ready to drop into your analysis scripts, spreadsheets, or dashboards. It turns the chaotic, opinionated world of YouTube comments into a clear signal for your projects.

What does this actor do?

YouTube Comments Scraper is a web scraping and automation tool available on the Apify platform. It's designed to help you extract data and automate tasks efficiently in the cloud.

Key Features

Cloud-based execution - no local setup required
Scalable infrastructure for large-scale operations
API access for integration with your applications
Built-in proxy rotation and anti-blocking measures
Scheduled runs and webhooks for automation

How to Use

Click "Try This Actor" to open it on Apify
Create a free Apify account if you don't have one
Configure the input parameters as needed
Run the actor and download your results

Documentation

YouTube Comments Scraper

Extract comments and replies from YouTube videos. This Apify actor collects comment text, author details, timestamps, likes, and engagement metrics, outputting structured data for analysis.

Categories: SOCIAL_MEDIA, VIDEOS, DEVELOPER_TOOLS

Overview

This tool scrapes YouTube comments for analytics, sentiment analysis, competitor research, or content strategy. It handles single videos or bulk lists, supports proxies, and exports data in JSON, CSV, or Excel formats.

Key Features

Complete Data Extraction: Gets comment text, author name & URL, timestamp, like count, reply count, hearted status, and pinned status.
Flexible Sorting: Filter comments by top, newest, or oldest.
Bulk Processing: Scrape multiple videos via a list of URLs.
Proxy Support: Built-in proxy configuration for reliable scraping.
Scalable: Includes controls for request delays and rate limits.
Multiple Export Formats: Output to JSON, CSV, Excel, or fetch via API.

How to Use

Sign up for a free Apify account.
Configure the actor's input (see below).
Run it. Download the results from the dataset.

Input Configuration

Configure the scraper using a JSON input. Here are basic and advanced examples.

Basic Input:

{
  "videoUrls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
  "maxComments": 1000,
  "sortBy": "top",
  "includeReplies": true
}

Advanced Input (Bulk with Proxy):

{
  "videoUrls": [
    {"url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"},
    {"url": "https://www.youtube.com/watch?v=jNQXAC9IVRw"}
  ],
  "maxComments": 500,
  "sortBy": "new",
  "includeReplies": true,
  "proxyConfig": {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]},
  "delayBetweenRequests": 2000
}

Input Parameters:
* videoUrls (String or Array): One or more YouTube video URLs.
* maxComments (Number): Maximum comments to scrape per video.
* sortBy (String): Sort order ("top", "new", or "old").
* includeReplies (Boolean): Whether to fetch reply comments.
* proxyConfig (Object): Configuration for Apify Proxy.
* delayBetweenRequests (Number): Delay in milliseconds between requests.

Output

The actor outputs an array of items, one per comment. Each item contains the following fields:

{
  "commentText": "This tutorial completely changed how I approach content creation!",
  "author": "Sarah Johnson",
  "authorUrl": "https://www.youtube.com/@sarahcreates",
  "publishedTime": "2025-01-15T14:30:00Z",
  "likeCount": 247,
  "replyCount": 12,
  "isHearted": true,
  "isPinned": false,
  "videoId": "dQw4w9WgXcQ"
}

Output Data Fields:

Field	Description
commentText	The full text of the comment.
author	The commenter's display name.
authorUrl	Link to the commenter's YouTube channel.
publishedTime	ISO timestamp of when the comment was posted.
likeCount	Number of likes the comment has received.
replyCount	Number of replies to the comment.
isHearted	Boolean indicating if the video creator hearted the comment.
isPinned	Boolean indicating if the comment is pinned.
videoId	The YouTube ID of the source video.

Use Cases

Sentiment Analysis: Process comment text for audience sentiment.
Competitor Analysis: Scrape comments from competitor videos to identify audience preferences.
Brand Monitoring: Track mentions and discussions about your brand or product.
Content Research: Analyze feedback to inform content strategy.
Academic Research: Gather data for social media or community behavior studies.