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4 Oct 2019

This bot read 3.5M books to find out how language perpetuates gender stereotypes

Stereotyping and bias — be that conscious or subconscious — is one of the leading contributors to the gender gap prevalent today. It’s time to identify and challenge the societal structure that systematically prevents women from thriving — one of these structures is gendered language and the patriarchal ideas built into it.

In August, a group of computer scientists from the University of Copenhagen and other universities used machine learning to analyze 3.5 million books, published between 1900 to 2008, to find out whether the language used to describe men and women differed — spoiler alert: it did.

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