Pinterest Comments Scraper 📊

🔍 Overview

This actor allows you to extract comments and engagement data from any Pinterest pin. It provides comprehensive information about comments, user interactions, and engagement metrics in a structured format.

✨ Features

• 🎯 Extract comments from any Pinterest pin URL
• 👤 Get detailed user information for each comment
• 📊 Collect engagement metrics (likes, helpful counts)
• 🖼️ Access associated image information and signatures
• 🔄 Handle rate limiting and pagination automatically
• 🚀 Fast and efficient data collection
• 📱 Works with both desktop and mobile Pinterest URLs

🎯 Use Cases

• 💡 Social media engagement analysis
• 📈 Content performance tracking
• 🔍 User sentiment analysis
• 🎨 Visual content research
• 📊 Influencer marketing research
• 🤝 Community engagement monitoring

💎 Output

The actor provides detailed JSON output including:

• Comment content and timestamps
• User details (username, profile info)
• Engagement metrics (likes, helpful counts)
• Associated images and their variations
• Comment thread structure
• Related tags and metadata

🔧 Input Parameters

• pinUrl: Pinterest pin URL to scrape comments from
• limit: Maximum number of comments to collect (default: 50)
• proxyConfiguration: (Optional) Proxy settings for the scraper

💡 Tips

• Use proxy configuration for better reliability
• Adjust the limit parameter based on your needs
• Consider rate limiting for large-scale scraping

Input

A full explanation of an input example in JSON.

{
    "pinUrl": "https://www.pinterest.jp/pin/636977941054343221/",
    "limit": 50 
}

Output sample

The results will be wrapped into a dataset which you can always find in the Storage tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

[
  {
    "pinUrl": "https://jp.pinterest.com/pin/636977941054343221/",
    "node_id": "VXNlckRpZEl0RGF0YTo1MzgzNDI5Mjc0MjUyMzkzODQ0",
    "helpful_count": 0,
    "tags": [],
    "videos": [],
    "comment_count": 0,
    "marked_helpful_by_me": false,
    "image_signatures": [
      "de258d5c5e1577b30c8744148baa2fc9"
    ],
    "user": {
      "node_id": "VXNlcjo4MTc0MDM1Mzg1MjYyMjYzOTQ=",
      "image_medium_url": "https://s.pinimg.com/images/user/default_75.png",
      "is_private_profile": false,
      "username": "alinaaskarova2855",
      "first_name": "Alina",
      "full_name": "Alina",
      "type": "user",
      "id": "817403538526226394"
    },
    "like_count": 0,
    "images": [
      {
        "originals": {
          "url": "https://i.pinimg.com/originals/de/25/8d/de258d5c5e1577b30c8744148baa2fc9.jpg",
          "width": 810,
          "height": 1080
        },
        "550x": {
          "url": "https://i.pinimg.com/550x/de/25/8d/de258d5c5e1577b30c8744148baa2fc9.jpg",
          "width": 550,
          "height": 733
        },
        "150x150": {
          "url": "https://i.pinimg.com/150x150/de/25/8d/de258d5c5e1577b30c8744148baa2fc9.jpg",
          "width": 150,
          "height": 150
        }
      }
    ],
    "type": "userdiditdata",
    "done_at": "Fri, 30 Aug 2024 05:04:21 +0000",
    "details": "",
    "liked_by_me": false,
    "id": "5383429274252393844"
  },
    ...
]

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