Name Game: Gender Prediction using Sound
The same name can be spelled out in a many ways (for example, Marc and Mark, or Elizabeth and Elisabeth). Sound can, therefore, be a better way to match names than spelling. In this project,I have used Python package Fuzzy to find out the genders of authors that have appeared in the New York Times Best Seller list for Children's Picture books.
First, using fuzzy (sound) name matching, I searched for author names in a dataset provided by the US Social Security Administration that contains names and genders of all individuals who have applied for Social Security Cards. Next, I aggregated the author dataset by including gender. Finally, I used the new dataset to plot the gender distribution of children's picture books authors over time.