genderizeR

by Kamil Wais homepage / contact

R package for gender predictions based on first names.

The package home page: https://kalimu.github.io/project/genderizer/

Information about the genderize.io project and documentation of the API: http://genderize.io

Description

The genderizeR package uses genderize.io API to predict gender from first names extracted from text corpus (not only from clean vectors of given names). The accuracy of prediction could be controlled by two parameters: counts of first names in database and probability of gender given the first name. The package has also built-in functions that can calculate specific errors (also with bootstrapping), train algorithm on training dataset (with gender labels) and prepare character vectors for gender checking.

Installing the package

Installing stable version from CRAN

install.packages('genderizeR')

Installing developer version from GitHub

Remember to install devtools package first!

# install.packages('devtools')
devtools::install_github("kalimu/genderizeR")

Loading the installed package

library(genderizeR)

#> 
#> Welcome to genderizeR package version: 2.0.0.9003
#> 
#> Homepage: http://www.wais.kamil.rzeszow.pl/genderizeR
#> 
#> Changelog: news(package = 'genderizeR')
#> Help & Contact: help(genderizeR)
#> 
#> If you find this package useful cite it please. Thank you!
#> See: citation('genderizeR')
#> 
#> To suppress this message use:
#> suppressPackageStartupMessages(library(genderizeR))

A working example

# An example for a character vector of strings
x = c("Winston J. Durant, ASHP past president, dies at 84",
"JAN BASZKIEWICZ (3 JANUARY 1930 - 27 JANUARY 2011) IN MEMORIAM",
"Maria Sklodowska-Curie")
 
# Search for terms that could be first names
# If you have your API key you can authorize access to the API with apikey argument
# e.g. findGivenNames(x, progress = FALSE, apikey = 'your_api_key')
givenNames = findGivenNames(x, progress = FALSE)

# Use only terms that have more than x counts in the database
givenNames = givenNames[count > 100]
givenNames
#>       name gender probability count
#> 1: winston   male        0.98   128
#> 2:     jan   male         0.6  1663
#> 3:   maria female        0.99  8402

# Genderize the original character vector
genderize(x, genderDB = givenNames, progress = FALSE)
#>                                                              text
#> 1:             Winston J. Durant, ASHP past president, dies at 84
#> 2: JAN BASZKIEWICZ (3 JANUARY 1930 - 27 JANUARY 2011) IN MEMORIAM
#> 3:                                         Maria Sklodowska-Curie
#>    givenName gender genderIndicators
#> 1:   winston   male                1
#> 2:       jan   male                1
#> 3:     maria female                1

Tutorial

For more comprehensive tutorial check the vignette in the package.

browseVignettes("genderizeR")

What's new in the package?

news(package = 'genderizeR')

See package help pages in R / Rstudio

help(package = 'genderizeR')
?textPrepare
?findGivenNames
?genderize

How to contribute to the package?

For bugs, updates and new functionalities:

Fork git repo https://github.com/kalimu/genderizeR and submit a pull request.

Feedback:

If you enjoy using the package you could write a short testimonial and send it to me. I will be happy to post in on the package homepage.

For any kind of feedback you can use the contact form here: https://kalimu.github.io/#contact

How to contact the package's author regarding research or commercial project?

Please use the contact form: https://kalimu.github.io/#contact

How to cite the package?

citation('genderizeR')
#> 
#> Wais K (2006). "Gender Prediction Methods Based on First Names
#> with genderizeR." _The R Journal_, *8*(1), 17-37. doi:
#> 10.32614/RJ-2016-002 (URL: http://doi.org/10.32614/RJ-2016-002),
#> <URL: https://doi.org/10.32614/RJ-2016-002>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {{Gender Prediction Methods Based on First Names with
#>           genderizeR}},
#>     author = {Kamil Wais},
#>     year = {2006},
#>     journal = {{The R Journal}},
#>     doi = {10.32614/RJ-2016-002},
#>     pages = {17--37},
#>     volume = {8},
#>     number = {1},
#>     url = {https://doi.org/10.32614/RJ-2016-002},
#>   }

Thank You for the citation!