IMDb scraper for popular movies by genre with ratings and cast data

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What this robot does
How to scrape IMDb popular movies by genre in 4 steps
What can you do with IMDb movie data?
What data does this IMDb scraper extract?
Frequently asked questions
Get more data by pairing with these robots

What this robot does

IMDb is the definitive database for film and television, cataloging over 10 million titles with ratings from more than 200 million registered users. Its genre-based popularity rankings surface the films audiences actually watch and rate - not just the ones critics review. For entertainment industry analysts studying genre trends, content creators researching audience preferences, and developers building recommendation engines, IMDb's genre pages are the richest public source of structured movie data.

This robot extracts popular movie listings from IMDb genre pages: titles, user ratings, vote counts, release years, runtimes, metascores, plot descriptions, poster images, and direct IMDb links. One extraction captures the full genre landscape - whether you are analyzing sci-fi blockbusters, indie dramas, or horror films - and delivers it in a format ready for data analysis.

What IMDb genre data extraction enables:

✓ Genre performance benchmarking: See how movies in a specific genre perform. Compare average ratings, vote counts, and runtimes to understand what audiences expect from each genre.
✓ Talent tracking: Extract director and cast data to map which filmmakers dominate specific genres. Identify directors whose genre films consistently outperform.
✓ Release pattern analysis: Study which months and years produce the highest-rated films in a genre. Seasonal release patterns differ dramatically between action blockbusters and indie dramas.
✓ Audience scale measurement: Vote counts on IMDb indicate audience reach. A film with 500K votes has fundamentally different market penetration than one with 5K votes, even at the same rating.

Position	Title	Year	Duration	Rating	Votes	Metascore	Description	Poster	IMDb Link
#1	The Shawshank Redemption	1994	142	9.3	2500000	82	Two imprisoned men bond over a number of years, finding solace and eventual redemption through acts of common decency.	thumbnail	imdb.com/title/tt0111161
#2	The Godfather	1972	175	9.2	1800000	100	The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant youngest son.	thumbnail	imdb.com/title/tt0068646
#3	The Dark Knight	2008	152	9.0	2600000	84	When the menace known as the Joker wreaks havoc and chaos on Gotham, Batman must accept one of the greatest psychological tests.	thumbnail	imdb.com/title/tt0468569
#4	Pulp Fiction	1994	154	8.9	1900000	67	The lives of two mob hitmen, a boxer, a gangster's wife, and a pair of diner bandits intertwine in four tales of violence and redemption.	thumbnail	imdb.com/title/tt0110912
#5	Forrest Gump	1994	142	8.8	1700000	82	The presidencies of Kennedy and Johnson, the Vietnam War, and American pop culture unfold from the perspective of an Alabama man with an IQ of 75.	thumbnail	imdb.com/title/tt0109830

How to scrape IMDb popular movies by genre in 4 steps

No IMDb API key and no subscription needed. The robot reads IMDb's genre pages and delivers structured movie data.

A free Browse AI account (no credit card required).
The URL of an IMDb genre or chart page.

Create your Browse AI account in under a minute. No credit card required. You will find this prebuilt robot in the robot library ready to use.

Paste the IMDb genre page URL

Navigate to IMDb and select a genre - action, comedy, drama, sci-fi, horror, thriller, or any other. You can also use IMDb chart pages or advanced search results. Copy the URL.

Run the robot

Click run. The robot loads the IMDb page and extracts every listed movie - title, rating, vote count, year, runtime, metascore, description, poster, and IMDb link.

Connect integrations or export your data

Your film dataset is ready. Export to Google Sheets for genre analysis, sync to Airtable for a movie database, or connect through Zapier to feed film data into recommendation tools or content platforms.

Ready to get started?

Try this robot free →

What can you do with IMDb movie data?

Structured film data from IMDb supports entertainment industry analysis and content strategy:

Genre trend reports: Build annual or quarterly reports on genre performance. Which genres are producing the highest-rated films? Where is audience interest growing?
Runtime analysis: Do longer films rate higher in certain genres? Extract runtime and rating data to study the relationship between film length and audience reception.
Director filmography analysis: Extract all films by specific directors to analyze their career trajectories - how ratings evolve over time and across genres.
Vote count as popularity proxy: Use IMDb vote counts to measure films' cultural penetration beyond box office numbers. Highly-voted films have broad audiences even after theatrical release.
Content acquisition research: Streaming platforms and distributors can analyze which genres and time periods have the highest-rated, most-voted films to guide licensing decisions.
Recommendation system training: Build datasets of genre-specific movies with ratings to train or test recommendation algorithms.

🎬

Entertainment industry professionals

Analyze genre trends, talent performance, and audience preferences using structured IMDb data. Build market intelligence for production and acquisition decisions.

📊

Data scientists and ML engineers

Create training datasets for movie recommendation systems or sentiment analysis from IMDb's rich rating and metadata.

📝

Film critics and content creators

Research genre landscapes for articles, reviews, and video content. Data-driven film analysis stands out from opinion-only criticism.

📺

Streaming platform strategists

Study audience preferences by genre, era, and rating to inform content licensing, original programming, and UI recommendation strategy.

What data does this IMDb scraper extract?

Each movie from IMDb genre pages provides:

Field	What it contains
Position	Ranking position on the IMDb genre page.
Title	Full title of the film.
Year	Year of theatrical release.
Duration	Film runtime in minutes.
Rating	Average user rating out of 10.
Votes	Total number of user ratings submitted.
Metascore	Critic score from Metacritic (0-100).
Description	Plot summary or brief description of the film.
Poster	Movie poster image thumbnail.
IMDb Link	Direct URL to the film's IMDb page.

Genre pages show movie summaries. For full cast lists, plot details, box office data, and user reviews, pair genre extraction with individual movie page scraping.

Frequently asked questions

Can I extract from multiple genres?
Run separate extractions for each genre page URL. Each extraction captures one genre's popular movies.

Does it include box office data?
IMDb genre listing pages typically show ratings, votes, metascores, and basic metadata. Box office figures are available on individual movie pages.

Can I extract TV shows too?
IMDb has separate pages for TV shows. Navigate to a TV genre page and the robot extracts whatever data is displayed.

How are the movies ranked?
IMDb's 'popular' rankings use a combination of user ratings, vote counts, and recency. The exact algorithm is proprietary to IMDb.

Is this IMDb scraper free?
Browse AI's free plan includes credits to run this robot. No credit card required.

Genre popularity is one angle - combine with box office and upcoming releases for comprehensive film market intelligence:

IMDb box office scraper - Complement genre popularity data with current box office performance for a commercial-plus-audience view of the film market.
IMDb upcoming releases scraper - Track what is coming next in your genres of interest alongside analyzing current popular films.
Booking.com reviews scraper - While not film-related, the same structured extraction approach works for reviews on travel platforms.

Analyze popular movies by genre with IMDb data

Titles, ratings, cast, directors - structured film data from IMDb genre pages.