Open AccessUsing genderize.io to infer the gender of first names: how to improve the accuracy of the inference
Author(s) -
Paul Sebo
Publication year - 2021
Publication title -
journal of the medical library association jmla
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.102
H-Index - 58
eISSN - 1558-9439
pISSN - 1536-5050
DOI - 10.5195/jmla.2021.1252
Subject(s) - inference , computer science , information retrieval , world wide web , data science , natural language processing , artificial intelligence
We recently showed that genderize.io is not a sufficiently powerful gender detection tool due to a large number of nonclassifications. In the present study, we aimed to assess whether the accuracy of inference by genderize.io can be improved by manipulating the first names in the database.
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