Estimating Gender Completeness in Wikipedia

Fuente: arXiv
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Main Authors: Patel, Hrishikesh, Chen, Tianwa, Bongiovanni, Ivano, Demartini, Gianluca
Format: Preprint
Published: 2024
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author Patel, Hrishikesh
Chen, Tianwa
Bongiovanni, Ivano
Demartini, Gianluca
author_facet Patel, Hrishikesh
Chen, Tianwa
Bongiovanni, Ivano
Demartini, Gianluca
contents Gender imbalance in Wikipedia content is a known challenge which the editor community is actively addressing. The aim of this paper is to provide the Wikipedia community with instruments to estimate the magnitude of the problem for different entity types (also known as classes) in Wikipedia. To this end, we apply class completeness estimation methods based on the gender attribute. Our results show not only which gender for different sub-classes of Person is more prevalent in Wikipedia, but also an idea of how complete the coverage is for difference genders and sub-classes of Person.
format Preprint
id arxiv_https___arxiv_org_abs_2401_08993
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Estimating Gender Completeness in Wikipedia
Patel, Hrishikesh
Chen, Tianwa
Bongiovanni, Ivano
Demartini, Gianluca
Computers and Society
Information Retrieval
Gender imbalance in Wikipedia content is a known challenge which the editor community is actively addressing. The aim of this paper is to provide the Wikipedia community with instruments to estimate the magnitude of the problem for different entity types (also known as classes) in Wikipedia. To this end, we apply class completeness estimation methods based on the gender attribute. Our results show not only which gender for different sub-classes of Person is more prevalent in Wikipedia, but also an idea of how complete the coverage is for difference genders and sub-classes of Person.
title Estimating Gender Completeness in Wikipedia
topic Computers and Society
Information Retrieval
url https://arxiv.org/abs/2401.08993