Goodreads Review Scraper: Extract Book Reviews, Ratings, and Reviewer Profiles

Goodreads Review Scraper pulls reviews from any book on Goodreads using their internal API. No login or authentication needed. Just paste in one or more book URLs, set how many reviews you want per book, and run.

You get structured data including review text, star ratings, reviewer profiles, shelf labels, and tags, ready to export as CSV or JSON for analysis.

Unlike scrapers that parse HTML, this actor talks directly to the same API Goodreads uses in its own interface, so results come back fast and in a consistent format.

Use cases

• Sentiment analysis: collect hundreds of reader reviews to train classifiers or run opinion mining on reader reactions to a book
• Author research: pull reviews for your own books or titles you compete with, and see what readers actually say
• Book recommendation engines: gather ratings and tags to power recommendation logic or similarity scoring
• Market research: analyze reader responses to new releases in a specific genre or category
• Academic research: build datasets of reader reviews for literary analysis or sociological studies
• Publishing decisions: check reader feedback on comparable titles before commissioning similar work

Input

Parameter	Type	Default	Description
bookUrl	string		Single Goodreads book page URL. Use for one book at a time.
bookUrls	array		List of Goodreads book page URLs, one per line. Use for batch runs across multiple books.
maxReviews	integer	100	Maximum reviews to collect per book. Hard cap of 1000.
timeoutSecs	integer	300	Overall actor timeout in seconds.
requestTimeoutSecs	integer	30	Per-request timeout in seconds.
proxyConfiguration	object	Datacenter (Anywhere)	Proxy type and location for requests. Supports Datacenter, Residential, Special, and custom proxies. Optional.

You can use bookUrl, bookUrls, or both at the same time. Duplicate URLs are ignored.

Example: single book

{
    "bookUrl": "https://www.goodreads.com/book/show/3.Harry_Potter_and_the_Sorcerer_s_Stone",
    "maxReviews": 100
}

Example: multiple books

{
    "bookUrls": [
        "https://www.goodreads.com/book/show/3.Harry_Potter_and_the_Sorcerer_s_Stone",
        "https://www.goodreads.com/book/show/5907.The_Hobbit",
        "https://www.goodreads.com/book/show/7260188-the-hunger-games"
    ],
    "maxReviews": 200
}

What data does this actor extract?

The actor stores results in Apify's dataset. Each entry is one review:

{
    "reviewId": "kca://review:goodreads/amzn1.gr.review:goodreads.v1.tI_H8-8bJGQv1O4IIOpeTA",
    "reviewUrl": "https://www.goodreads.com/review/show/2280609898",
    "reviewText": "<b>4.5 Stars!</b><br /><br />Buddy read with...",
    "reviewTextPlain": "4.5 Stars! Buddy read with the one who started it all!...",
    "rating": 4,
    "createdAt": "2018-02-01T20:15:18+00:00",
    "updatedAt": "2021-02-19T16:45:57+00:00",
    "lastRevisionAt": "2018-03-20T18:24:36+00:00",
    "spoilerStatus": false,
    "likeCount": 114,
    "commentCount": 17,
    "recommendFor": null,
    "userId": 44125660,
    "userName": "Beth",
    "userUrl": "https://www.goodreads.com/user/show/44125660-beth",
    "userImageUrl": "https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/users/...",
    "isAuthor": false,
    "userFollowersCount": 627,
    "userTextReviewsCount": 929,
    "shelfName": "read",
    "shelfDisplayName": "Read",
    "shelfUrl": "https://www.goodreads.com/review/list/44125660?shelf=read",
    "tags": ["2018-reads", "audiobook", "book-series", "4-stars", "young-adult-fantasy"],
    "workId": "kca://work/amzn1.gr.work.v1.TbpxJa2CwiSSz_9W2FruoA",
    "scrapedAt": "2025-01-15T10:30:00+00:00"
}

Field	Type	Description
reviewId	string	Unique review identifier
reviewUrl	string	Direct link to the review
reviewText	string	Full review text with HTML markup
reviewTextPlain	string	Review text with HTML stripped
rating	integer	Star rating (1 to 5, or null if no rating given)
createdAt	string	When the review was first posted
updatedAt	string	When the review was last updated
lastRevisionAt	string	When the review text was last revised
spoilerStatus	boolean	Whether the review is flagged as a spoiler
likeCount	integer	Number of likes
commentCount	integer	Number of comments
recommendFor	string	Who the reviewer recommends the book for, if set
userId	integer	Reviewer's numeric ID
userName	string	Reviewer's display name
userUrl	string	Link to the reviewer's profile
userImageUrl	string	Reviewer's profile picture URL
isAuthor	boolean	Whether the reviewer is a published author on Goodreads
userFollowersCount	integer	How many followers the reviewer has
userTextReviewsCount	integer	Total reviews written by the reviewer
shelfName	string	Shelf slug (e.g. read, currently-reading)
shelfDisplayName	string	Human-readable shelf name (e.g. Read)
shelfUrl	string	Link to the reviewer's shelf
tags	array	Custom shelf tags applied by the reviewer
workId	string	The book's internal Goodreads identifier
scrapedAt	string	When this review was collected

How it works

1. The actor fetches each book page URL and extracts the internal book identifier from the page
2. It then calls the Goodreads API using cursor-based pagination to collect reviews page by page
3. Each page returns up to 30 reviews; the actor keeps fetching until it hits your maxReviews limit or runs out of reviews
4. For batch runs, the actor processes each book in order and pushes all results into the same dataset
5. Each review is pushed to the dataset as it arrives

FAQ

Do I need a Goodreads account to use this? No. The actor requires no login or personal credentials.

How many reviews can I collect per run? Up to 1000 per book. If you pass 5 book URLs with maxReviews: 200, you can collect up to 1000 reviews total in that run.

Does this work for all books on Goodreads? It works for any book with publicly visible reviews on Goodreads.

Integrations

Connect Goodreads Review Scraper with other apps using Apify integrations. You can pipe results into Google Sheets, send notifications via Slack, trigger workflows in Make or Zapier, or sync with Airbyte. You can also use webhooks to trigger actions as soon as results are ready.