📚 TL;DR: This tool lets you input up to five of your favourite books and receive an estimate of the gender bias you are likely exposed to. It'll then give you book recommendations that invert that bias, in order to expand your reading! Try it out by entering one of your favourites in the input above.
We are, each of us, caught within an echo chamber that unconsciously influences our understandings and beliefs. A couple of years ago I released "Break The Bubble", a tool which saught to give book recommendations outside of your echo chamber. This newer tool, however, is specifically about gender bias.
Imagine sitting in a library of limited size, tailored perfectly to your tastes. If we look at all the books in this library, the genders of their authors, and the genders of characters within the books, then we can find your "literary gender bias". That's what this tool attempts to do.
It is best to input 3 to 5 of your favourite books so that we can create the seeds of this hypothetical library. We will then extrapolate, calculate and show you your gender bias, and a set of recommendations that seek to invert that bias. It's much easier to show than tell, so here are some examples:
- Gender-bubble-breakers for topics of Economics & Technology »
- Gender-bubble-breakers for readers of Pride and Prejudice by Jane Austen »
- Gender-bubble-breakers for readers of Harry Potter »
- Gender-bubble-breakers for readers of Sci-Fi (e.g. Dune) »
- Gender-bubble-breakers for readers of 1Q84 by Haruki Murakami »
More details about implementation: Over 150,000 books have been given a very approximate score based on the names of the authors (compared against 80k locale-specific names) and the frequency and density of pronouns used in descriptions and in many millions of reviews of the books. This gives a very broad picture of the gender-bias space, but obviously lacks accuracy for any specific title. Nonetheless it enables us to build a general picture because books tend to be in "affinity spaces" with similar books. You can read more about how recommendations are made in a general sense on abooklikefoo.com as this uses the same backing data and hueristics.
Gentle disclaimer: This is an experimental tool I created just for my own curiousity. It is inherently limited in accuracy and due to implementation is unable to discern non-binary genders.
Want to break other literary echo-chambers? See my broader tool, "Break The Bubble".
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