Infers state-recorded gender categories from first names and dates of birth using historical
datasets. By using these datasets instead of lists of male and female names,
this package is able to more accurately infer the gender of a name, and it
is able to report the probability that a name was male or female. GUIDELINES:
This method must be used cautiously and responsibly. Please be sure to see the
guidelines and warnings about usage in the 'README' or the package documentation.
See Blevins and Mullen (2015) <http://www.digitalhumanities.org/dhq/vol/9/3/000223/000223.html>.

Predict Gender from Brazilian First Names
A method to predict and report gender from Brazilian first names
using the Brazilian Institute of Geography and Statistics' Census data.

dplyr (>= 0.5.0), jsonlite, httr, magrittr, purrr, tibble

A method to predict and report gender from Brazilian first names
using the Brazilian Institute of Geography and Statistics' Census data (<https://censo2010.ibge.gov.br/nomes/>).

Client for the Genderize API That Determines the Gender of Names
API client for genderize.io which will tell you the gender of the
name you input. Use the first name of the person you are interested in to find
their gender.

person("Kamil", "Wais", email = "kamil.wais@gmail.com", role =
c("aut", "cre"))
Utilizes the genderize.io API to predict gender from first
names extracted from a text vector. The accuracy of prediction could be
controlled by two parameters: counts of a first name in the database and
probability of prediction.
jsonlite, stringr, tm, data.table, magrittr, RCurl, parallel

stringr, httr, tm, data.table, magrittr, parallel

Utilizes the 'genderize.io' API to predict gender from first
names extracted from a text vector. The accuracy of prediction could be
controlled by two parameters: counts of a first name in the database and
probability of prediction.
stringr, httr, tm, data.table, magrittr, parallel, utils

c(person("Kamil", "Wais", email = "kamil.wais@gmail.com", role =
c("aut", "cre")), person("Nathan", "VanHoudnos", role = "ctb"), person("John", "Ramey", role = "ctb"))
Utilizes the 'genderize.io' Application Programming Interface
to predict gender from first names extracted from a text vector.
The accuracy of prediction could be controlled by two parameters:
counts of a first name in the database and probability of prediction.
Kamil Wais [aut, cre],
Nathan VanHoudnos [ctb],
John Ramey [ctb]