IMDb Review Scraper

📌 What review data can you collect from IMDb?

This template collects review records with Title, Review Title, User Name, Page URL, Premalink, Rating, Rating Count, and Review Rating. It is useful for customer-insight teams, reputation analysts, researchers, and competitive-intelligence professionals.

Data is collected from IMDb. IMDb is a database of movies, television, cast and crew information, ratings, and user reviews.

💰 Pricing

This template is currently free of charge and has no per-line usage fee. Octoparse plan or resource limits may still apply.

📦 Output

IMDb Review Scraper returns these fields:

• Title
• Rating
• Rating_Count
• Plot
• Page_URL
• Published_Year
• Length
• Director
• Writers
• Stars
• Review_Rating
• Review_Count
• User_Name
• Review_Date
• Review_Title
• Premalink
• Review_Text
• Helpful_Count
• Dislike_Count

{
  "Title": "Harry Potter and the Sorcerer's Stone",
  "Rating": "7.7 /10",
  "Rating_Count": "885K",
  "Plot": "An orphaned boy enrolls in a school of wizardry, where he learns the truth about himself, his family and the terrible evil that haunts the magical world.An orphaned boy enrolls in a school of wizardry, where he learns the truth about himself, his family and the terrible evil that haunts the magical world.An orphaned boy enrolls in a school of wizardry, where he learns the truth about himself, his family and the terrible evil that haunts the magical world.",
  "Page_URL": "https://www.imdb.com/title/tt0241527/?ref_=tt_urv",
  "Published_Year": "2001",
  "Length": "2h 32m",
  "Director": "Chris Columbus",
  "Writers": "J.K. RowlingSteve Kloves",
  "Stars": "Daniel RadcliffeRupert GrintEmma Watson",
  "Review_Rating": "8 /10",
  "Review_Count": "2,046 reviews",
  "User_Name": "Keyan-the-Eagle144",
  "Review_Date": "2018/03/23",
  "Review_Title": "The major start of all the magic!",
  "Premalink": "https://www.imdb.com/review/rw4101904/?ref_=tturv_perm_1",
  "Review_Text": "Having read the first few Harry Potter books before 2001 and hearing about the hype for the first movie, I was excited. I heard there was going to be an all-British cast (which makes sense, right?) and we'd get to see a live version of one of the defining novels of our generation. From what I remember I went with my family and a family friend to see the movie the day after Christmas and was pleasantly amazed. After the movie was over, I watched the credits and discovered some familiar names (the late Alan Rickman, Sister Act's Maggie Smith, James Bond 007's Robbie Coltrane, and Star Wars' Warwick Davis); others not so familiar (the kids, some of whom had their debut). But it was a good movie and was a party of colors and sights for all to see. This is easily my favorite of all the Harry Potter films. The catalyst of the movie series!",
  "Helpful_Count": "83",
  "Dislike_Count": "13"
}

🎯 Use Cases

• Build a structured IMDb review dataset organized by Title, Review Title, and User Name.
• Compare Rating, Rating Count, Review Rating, and Review Count across collected records.
• Analyze review content through Review Text and review timing through Review Date.
• Measure audience response using Dislike Count and Helpful Count.

🐙 Why Octoparse

• Built for IMDb: The automation opens each page supplied through URL (up to 50,000 per run), moves through the available review content according to the configured controls, and writes structured review rows including Title, Rating, Rating Count, and Plot.
• Inputs match the workflow: The form uses URL (up to 50,000 entries).
• Fields stay connected: IMDb Review Scraper returns Title, Page_URL, Rating, Review_Date, and Review_Text in the same structured dataset.
• Ready for repeat use: After IMDb Review Scraper runs locally or in the cloud, schedule eligible tasks and export the rows for spreadsheets, dashboards, APIs, or AI workflows.

📝 Input

Complete the following fields:

• URL (Required) — Enter a list of movie URLs for review extraction. Up to 50,000 entries per run.

🚀 How to Use

1. Open IMDb Review Scraper and click Try it!.
2. Complete URL using the formats and limits shown in the Input section.
3. Choose a local or cloud run in Octoparse and start the task.
4. Review fields such as Title, Page_URL, and Rating, then export the rows in the format you need.

💡 Tips

• Test one representative value in URL before submitting a large batch to IMDb Review Scraper.
• Keep Page_URL in the export so every row can be traced to its originating input or page.

❓ FAQ

How many entries can IMDb Review Scraper accept in URL per run?

Enter up to 50,000 values in URL per run.

Which IMDb pages does IMDb Review Scraper process?

The workflow is configured for review pages and returns fields such as Title, Page_URL, Rating, and Review_Date.

What can I use data from IMDb Review Scraper for?

Build a structured research dataset organized by Title, Review Title, and User Name.

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