Data as of Aug 25, 2026 · Based on 323 AI responses from ChatGPT Search and Google AI Mode · See how Parse measures this
For personalized, mood- or pace-aware recommendations use The StoryGraph; for tracking your reading, broad community reviews, and finding popular or reader-curated lists use 
Named in 80% of answers
Best when you want to track reading, read wide community reviews, and browse popular or reader-curated lists—Goodreads excels at tracking and community-sourced suggestions; add StoryGraph for deeper mood/pacing filters.
Named in 64% of answers
Named in 62% of answers
Best when you want recommendations tuned to mood, trope, pacing and reading-history analysis—StoryGraph emphasizes personalized suggestions based on how you read; pair with Goodreads if you need community lists or tracking.
Named in 56% of answers
Source | Citation share |
|---|---|
 Finding book recommendations online - Finding fiction (and other books) to read for fun - Research Guides at New York Universityhttps://guides.nyu.edu/readforfun/recommendations | 4.2% |
 How do you find new books? - Reddithttps://www.reddit.com/r/books/comments/16d07hg/how_do_you_find_new_books/ | 4.0% |
 Finding the Perfect Book to Read Next – TCEA TechNotes Bloghttps://blog.tcea.org/finding-the-perfect-book-to-read-next/ | 3.4% |
What websites do you use for book recommendations? - Reddithttps://www.reddit.com/r/books/comments/txqn1r/what_websites_do_you_use_for_book_recommendations/ | 2.5% |
 5 Tips For Choosing Books To Read | Lucid Bookshttps://lucidbooks.com/5-tips-for-choosing-books-to-read/ | 2.3% |
 Whichbookhttps://www.whichbook.net/ | 2.3% |
 What are the Best Book Recommendation Websites?https://www.bookbrowse.com/blogs/editor/index.cfm/2025/4/21/What-are-the-Best-Book-Recommendation-Websites | 2.2% |
how to find your next book to read - by caitlyn - milk fedhttps://caitlynrichardson.substack.com/p/how-to-find-your-next-book-to-read | 2.2% |
 17 Ways To Find Good Books To Read - Cushing-Malloyhttps://cushing-malloy.com/2019/12/02/17-ways-to-find-good-books-to-read/ | 2.0% |
Goodreadshttps://www.goodreads.com/ | 2.0% |
The best recommendations usually come from **combining personalized algorithms with human-curated lists** rather than relying on bestseller lists alone. - **Use [thestorygraph.com](https://www.thestorygraph.com/?utm_source=chatgpt.com)** if you want recommendations based on *mood, pace, themes, genre,* and your past…
The best recommendations usually come from combining personalized algorithms with human-curated lists rather than relying on bestseller lists alone.
And honestly, you can use me as a personalized book recommender. Give me 3–5 books you've loved, 1–3 you've disliked, and tell me whether you're looking for fiction, nonfiction, or either. I can then give you a short list tailored to why you liked those books, rather than just matching genres.
Finding your next great read comes down to matching your mood, favorite tropes, or curiosity style with the right discovery engine. Here are the best ways to unearth incredible books, broken down by how they work: - Platform Communities & Trackers: Use Goodreads for massive user databases and reviews, or try…
Finding your next great read comes down to matching your mood, favorite tropes, or curiosity style with the right discovery engine. Here are the best ways to unearth incredible books, broken down by how they work:
If you want to kickstart your reading list right now, tell me:
I can give you a customized list of recommendations to start with!
The best way is **not to rely on a single “best books” list**. Good recommendations come from matching books to *your* tastes. Here’s a method that works well: - **Start with books you already loved.** Write down 3–5 books you genuinely enjoyed and, importantly, *why* you liked them: the writing, characters, ideas,…
The best way is not to rely on a single “best books” list. Good recommendations come from matching books to your tastes.
Here’s a method that works well:
Tell me 5 books you've read and how you felt about each one—even something as simple as:
Loved: The Martian, Gone Girl Liked: Dune Didn't finish: The Name of the Wind Hated: [book] Want more: suspense + clever ideas, but not 800-page books I can use that to give you a personalized reading list, explain why each book fits, and include a few deliberately unexpected picks so you don't end up reading the same 20 books everyone recommends.
Finding great book recommendations depends on whether you want data-driven algorithms, deep human-curated expert lists, or interactive community spaces. Here are the best avenues to explore: - **Algorithm and Data-Driven Platforms:** Websites like [The StoryGraph](https://app.thestorygraph.com/) offer mood-based and…
Finding great book recommendations depends on whether you want data-driven algorithms, deep human-curated expert lists, or interactive community spaces. Here are the best avenues to explore:
If you want to kick things off, tell me:
I can give you a few tailored recommendations right now!
Finding your next great read is all about tapping into communities, algorithms, and expert curators that match your specific taste. Here are the best ways to discover books you'll actually love: - **Social Reading Platforms:** Use [Goodreads](https://www.goodreads.com/) to track your reading, see what friends are…
Finding your next great read is all about tapping into communities, algorithms, and expert curators that match your specific taste. Here are the best ways to discover books you'll actually love:
What Readers Say
I found The StoryGraph to be a game changer because of the mood and pace tags. It really helps when I'm looking for a very specific vibe.
r/suggestmeabook on Reddit is unmatched; people will give you the most thoughtful, specific lists you've ever seen.
To narrow it down, let me know:
I can give you a personalized starter list right now.
The best approach is to **combine personalized recommendation tools with human-curated lists**. No single site is consistently great at knowing your taste. ### My recommended workflow 1. **Start with books you already love.**
The best approach is to combine personalized recommendation tools with human-curated lists. No single site is consistently great at knowing your taste.
Start with books you already love.
Give a recommendation engine 3–5 books you genuinely enjoyed, rather than just entering a genre. This produces much better results than “best books in sci-fi,” for example.
Try StoryGraph for personalization.
It lets you filter by things like mood, pacing, genre, and other characteristics, and readers frequently praise its discovery/filtering features.
Use Goodreads mainly for reviews and breadth.
It has an enormous user base and lots of reviews, so it's useful for checking whether a promising book actually resonates with readers—but its recommendations can be hit-or-miss.
Look at curated recommendations from publications.
NPR's Books We Love is particularly good: it has thousands of recommendations and lets you filter by genre, topic, year, and qualities such as “seriously great writing.”
Ask actual readers with a very specific prompt.
Reddit can be surprisingly good when you say something like:
“I loved X because of its atmosphere and Y because of its characters. I don't want anything overly violent. What should I read?”
Genre-specific communities tend to be more useful than generic “what should I read?” posts. Recent readers also report using Reddit alongside StoryGraph for discovery.
Instead of asking “What are the best books?”, ask:
“What books are similar to these 3 books, but different in this specific way?”
That forces recommendations toward your taste rather than popularity.
And you can use me for this too. Give me 3–5 books you loved, 1–2 you disliked, and what you liked/disliked about them, and I can build you a much more targeted reading list.
The best approach is **not to rely on one recommendation list or one algorithm**. Good recommendations come from combining a few different signals. ### A good system for finding books 1. **Start with books you loved, not just genres.**
The best approach is not to rely on one recommendation list or one algorithm. Good recommendations come from combining a few different signals.
Start with books you loved, not just genres.
“I like fantasy” is broad; “I loved Piranesi because it was strange, atmospheric, and short” gives much better information. Recommendations based on why you liked something tend to be more useful.
Use The StoryGraph for personalized discovery.
It lets you filter by mood, pace, genre, themes, and other characteristics, and its recommendation system uses your reading preferences. You can also import your Goodreads history.
Use Goodreads when you want lots of reader opinions.
Its huge community makes it particularly useful for seeing what readers who liked a particular book also enjoyed, browsing reviews, and finding niche lists. Goodreads' recommendation system has historically used users' shelves, ratings, and relationships between books.
Ask a person—or me—with a very specific prompt.
This is often surprisingly effective. Instead of:
“Recommend me some good books.”
Try:
“I loved Project Hail Mary and The Martian. Give me 8 books with clever problem-solving and high stakes, but no military thrillers. Explain why I'd like each one.”
You can even give me 3 books you loved and 2 you disliked, which is often enough for me to identify patterns in your taste.
Keep a tiny “taste profile.”
Whenever you finish a book, record:
After 10–20 books, you'll have much better recommendation data than simply knowing your favorite genres.
I'd combine StoryGraph + human recommendations:
Track what you read → identify what you actually liked about it → get 5–10 targeted recommendations → pick one that sounds exciting → repeat.
And don't feel obligated to finish books you aren't enjoying. Marking books as DNFs and noting why can actually make future recommendations better.
If you'd like, give me 3–5 books you've loved recently (and optionally one you hated), and I'll figure out your reading taste and recommend your next 10.
The best way to find good book recommendations is to `combine personalized online databases like Goodreads and The StoryGraph with human-curated resources such as Five Books and your local public library` . Tracking your preferences through platforms that match your specific reading moods or asking communities with…
The best way to find good book recommendations is to combine personalized online databases like Goodreads and The StoryGraph with human-curated resources such as Five Books and your local public library . Tracking your preferences through platforms that match your specific reading moods or asking communities with similar tastes yields much higher quality suggestions than generic bestseller lists.
Digital Tracking and Discovery Platforms
Expert and Human-Curated Sources
Community Perspectives
“I get books from Audible when my library won't have it for a while or only has the ebook version. Or doesn't carry an author I particularly like. I get books from Libby.”
“I started using StoryGraph to track my books. I find the recommendations it gives have been pretty spot on.”
If you tell me two or three books or movies you really enjoyed recently , and what genre you are in the mood for , I can give you a custom list of specific book recommendations to start with.
Finding your next great read is all about tapping into communities, algorithms, and expert curators that match your specific taste. Here are the best ways to find fantastic book recommendations: - **Goodreads:** The largest social network for readers. Use it to track what you read, rate books, and get personalized…
Finding your next great read is all about tapping into communities, algorithms, and expert curators that match your specific taste. Here are the best ways to find fantastic book recommendations:
If you'd like to get started, tell me:
I can give you a customized list of recommendations right now!
The **best way is to combine a few different sources**, rather than trust one recommendation algorithm. Different systems are good at different things. ### My favorite approach 1. **Start with 3–5 books you already loved.**
The best way is to combine a few different sources, rather than trust one recommendation algorithm. Different systems are good at different things.
Start with 3–5 books you already loved.
Tell me the titles—and ideally what you liked about them. “I loved the atmosphere but hated the romance” is much more useful than a genre label.
Use StoryGraph for discovery.
It lets you search/filter by things like mood, pacing, genre, and other characteristics. Readers frequently praise it specifically for its filtering and recommendation features.
Use Goodreads for breadth and reader reviews.
Its enormous user base and lists make it particularly useful for finding books related to a specific title, author, or niche.
Ask actual readers on Reddit.
Communities such as r/books and genre-specific communities can be surprisingly good when you have a very specific request—e.g. “books like Piranesi but less fantastical.”
Look at award shortlists.
This is one of the best ways to escape the algorithmic “same 50 popular books” bubble. Hugo/Nebula, Booker, National Book Award, International Booker, etc. are great starting points. Readers also recommend award lists as a discovery method.
Ask me with constraints.
This is probably the easiest option if you want curated rather than popular recommendations. Give me:
I can then give you 5–10 recommendations with an explanation of why each fits, rather than just throwing a bestseller list at you.
One particularly effective trick: don't ask for “books like X.” Ask for “books that capture the thing I loved about X.” A book you love might be memorable because of its prose, humor, characters, ideas, setting, tension, or emotional effect—and those can lead to much better recommendations than genre alone.
If you give me 3 books you loved and 1 you hated, I can start building you a personalized reading list.
