IMDb User Reviews Scraper

Extract every user review for any movie or TV title on IMDb, with star rating, full text, author, helpfulness votes and spoiler flags, plus the title's aggregate rating and per-star breakdown.

21 fields per record

Global coverage

JSON / CSV / Excel output formats

Updated 2026-07-26

What you get

Give the scraper one or more IMDb titles (a title ID like tt0111161 or a full title URL) and it returns each user review as its own record, sorted by helpfulness, date, user rating or total votes. Every record also carries the title's own aggregate rating and vote breakdown so you can analyse reviews in context.

• imageUrl: the title's poster image URL
• reviewTitle: the review headline the author wrote
• reviewId: the IMDb review ID
• rating: the reviewer's star rating out of 10 (empty when the reviewer left no rating)
• author: the reviewer's username
• authorUrl: link to the reviewer's IMDb profile
• reviewDate: the date the review was submitted
• helpfulUpVotes: how many users found the review helpful
• helpfulTotalVotes: total helpfulness votes cast on the review
• spoiler: whether the review is flagged as containing spoilers
• reviewText: the full review text
• permalink: a direct link to the review on IMDb
• imdbId: the title ID the review belongs to
• titleName: the movie or TV title name
• titleYear: the title's release year
• titleUrl: link to the title on IMDb
• titleRating: the title's aggregate IMDb rating
• titleVotes: the title's total number of rating votes
• titleRatingBreakdown: per-star vote distribution for the title (how many votes at each score from 1 to 10)
• observedAt: when this review was last seen by the scraper

Who is it for

Use case	Who benefits
Sentiment analysis on a film or series	Data scientists and researchers
Tracking audience reaction to a new release	Studios and streaming teams
Building a movie recommendation dataset	ML engineers
Monitoring reviews and ratings over time	Media analysts
Sourcing quotes and audience opinions	Journalists and content teams

Frequently Asked Questions

Which titles does this cover?
Any movie, TV series, episode or short that has a page on IMDb worldwide. You reference a title by its ID (the tt code in its URL, for example tt0111161) or by pasting the full title URL. You can submit many titles in one run.

How many reviews can I collect per title?
Set the Max Reviews Per Title value to any number. Popular titles have tens of thousands of reviews and the scraper pages through them until it reaches your limit or runs out. On free Apify plans the per-title count is capped; upgrade for the full set.

Can I control the order reviews come back in?
Yes. Choose Most helpful, Newest first, User rating or Total votes, in ascending or descending direction. Most helpful descending returns the reviews the community found most useful first.

Does it include the star rating and spoiler flag?
Yes. Each review carries the reviewer's 1 to 10 star rating (left empty when the reviewer wrote a review without scoring), a spoiler flag, and the helpful and total vote counts. Every record also includes the title's aggregate rating and full per-star vote breakdown.

What happens if a title has no reviews or the ID is wrong?
The scraper reports the title cleanly and moves on to the next one. Records that could not be retrieved carry an error field so nothing silently disappears from your dataset.

More scrapers at scrapers.lat

This actor is built and maintained by scrapers.lat, where we publish scrapers for Latin American and US public platforms: real estate, jobs, e-commerce, company registries and government data. Browse the full catalog, see live sample output for each one, or ask us for a custom scraper at scrapers.lat.

---

This actor is an independent tool and has no affiliation with IMDb. It only accesses data that is publicly available on the platform. Use it in accordance with IMDb's terms of service.