IMDB Reviews Scraper 🎬

This actor scrapes detailed user reviews from IMDB movie/TV show pages. It's perfect for sentiment analysis, audience feedback collection, and content research. 🎯

Features ✨

• 🔍 Scrapes complete user reviews with ratings
• 👤 Captures reviewer details and profile links
• 📊 Includes helpfulness votes data
• 📅 Records submission dates
• 🚀 Handles pagination automatically
• ⚡ Fast and efficient with built-in proxy support
• 🛡️ Uses advanced browser automation to bypass restrictions

Use Cases 💡

• Content Analysis: Analyze audience reception and sentiment
• Market Research: Understand viewer preferences and trends
• Data Collection: Gather structured review data for ML/AI training
• Competitive Analysis: Track reception of different shows/movies
• Academic Research: Study audience behavior and opinions

Output Data Structure 📋

The actor outputs detailed review data including:

• Review text and summary
• Author information (nickname, user ID, profile URL)
• Rating score (0-10)
• Submission date
• Helpfulness metrics (upvotes/downvotes)
• Spoiler flags
• Original review URLs

Input Parameters 🎮

• reviewPageUrls: Array of IMDB review page URLs to scrape
• maxItems: Maximum number of reviews to collect (optional)
• proxyConfiguration: Proxy settings (optional, recommended for large-scale scraping)

Tips for Optimal Usage 💪

1. Use proxy configuration for better reliability
2. Set reasonable maxItems limit based on your needs
3. Respect IMDB's terms of service and rate limits
4. Consider using multiple runs for large datasets

Input Example

A full explanation of an input example in JSON.

1{
2    "reviewPageUrls": [
3        "https://www.imdb.com/title/tt11280740/reviews/?ref_=tturv_ql_2"
4    ],
5    "maxItems": 30
6}

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.

1[
2    {
3        "reviewPageUrl": "https://www.imdb.com/title/tt11280740/reviews/?ref_=tturv_ql_2",
4        "id": "rw8043079",
5        "authorNickName": "doomedmac",
6        "authorUserId": "ur111092901",
7        "authorUrl": "https://www.imdb.com/user/ur111092901",
8        "summary": "This is brilliant",
9        "text": "I can't remember the last time I was so invested in a TV show. I was hooked from the first episode, and constantly impressed with the directing, visuals, acting, and plot developments. It's like a cross between Black Mirror and 1984, but it might be better than both of those works of art. This is truly something special and I COULD NOT be more excited for season 2.",
10        "authorRating": 9,
11        "submissionDate": "2022-04-08",
12        "helpfulnessUpVotes": 1147,
13        "helpfulnessDownVotes": 125,
14        "spoiler": false,
15        "reportingLink": "https://contribute.imdb.com/review/tt11280740/rw8043079/report?bus=imdb&return_url=https%3A%2F%2Fwww.imdb.com%2Fclose_me&site=web"
16    },
17    ...
18]

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