How to Use Algorithms to Personalize Your Book Recommendations

Algorithms can work against us when someone is pulling the strings behind the curtain. I think our reading lives— or better said, the use of our time— is too important to leave to algorithms. 

One way to fight this is to be intentional about the use of our time, do the research and only read what is beneficial. 

Another option is to make the algorithms work for you. 

My top pick for a resource to use algorithms to find personalized book recommendations is The StoryGraph and the most important factor is to tailor your input to get the best results.  

Besides The StoryGraph, I’ve listed what I like and don’t like about websites that use algorithms to recommend books.

According to Bookriot, “if you’re someone who is only interested in keeping up with the newest bestsellers, Goodreads is great. However, if you’re more interested in finding specific books that you know you’ll love, Storygraph is by far the better option.”

I agree.

What I Like about The StoryGraph

Content warnings.

This is huge for me. They are reader submitted, with three levels–graphic, moderate and minor. There’s also a place for author submitted content warnings. 

The different moods of a book are rated– such as reflective, sad, emotional or inspiring. This is wonderful info to have about a book.

It’s nice to know about the pace of a book, whether it’s slow moving or fast moving.

Information about character and plot. Are the characters likable? flawed? Was the ending sad?

It has short ratings and full reviews.

It’s not associated with Amazon or Goodreads.

You can transfer Goodreads data over to your StoryGraph account.

Possibilities for good recommendations is higher, in my opinion, especially for fiction. When you’re reading to escape or relax, different factors are important than when you’re reading to learn.

What I Don’t Like about The StoryGraph

It has a 5 star rating system, although half stars and even quarters stars are an option. 

use algorithms

What I Like about Readgeek

It has 10 point rating system with half point options. It’s quick to rate, with an easy slide scale.

Lovers also liked list for each book. 

Personal predicted rating is interesting. 

What I don’t Like about Readgeek

Most of their recommendations don’t feel like a good fit for me. Maybe I don’t have enough data in with 73 books rated or maybe I wasn’t strategic enough about the books I chose. 

Readgeek has a beta after the name, which could mean that bugs and glitches are still being worked out.

What I Like about Goodreads

Readers also enjoyed feature for each book.

More readers are on Goodreads

What I Don’t Like about Goodreads

5 star rating system with no half stars.

It’s owned by Amazon, which has it’s pros and cons

What I Like about Literature Map

It’s so cool!

Put in a favorite authors’ name and then watch the other names circle around. It’s just plain fun to watch. 🙂

Finding a new favorite author can be more valuable than finding a new favorite book. 

What I Like about Amazon

It’s people also bought feature.

Amazon Best Seller Ranking, so you can see how well the book is selling.

Author Bios.

Reader reviews, specifically how high the books are rated and what people have to say about them. 


The bottom line is that the more precise information you feed your algorithm, the better it will work for you. Mixing more than one person’s preference will mess with the results.

Another good strategy for finding books you love is nailing down your favorite book genre. Read my step by step here.

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