Published June 2021 | Version v1
Thesis Restricted

The Analysis of Gender-Bias towards Children in Amazon Customer Reviews

Creators

  • 1. University of Chicago

Contributors

Committee member:

Description

Girls have been biased against throughout history. Although progress in gender equality has been made, such biases still exist all over the world. But, unlike in the past, when gender biases towards kids were explicitly shown, nowadays, people may unconsciously or implicitly hold gender biases towards children. These biases are embedded in their words and are not easily revealed. Utilizing Customer data from Amazon customer reviews and a word embedding algorithm, I analyze whether there are gender biases and stereotypes towards children within a close relationship and within the general society explicitly and implicitly. I also examine how such biases occur, whether it is because of the positive bias against boys or negative bias against girls. Finally, I show that if gender biases and stereotypes towards children do exist, how they differ between the US and the UK.

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Additional details

Identifiers

Other
oai:uchicago.tind.io:2879

UChicago Information

Division(s)
Social Sciences Division
Department(s)
Computational Social Sciences (MACSS)