Monitoring the gender gap with Wikidata human gender indicators

Maximilian Klein, Harsh Gupta, Vivek Rai, Piotr Konieczny, Haiyi Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

The gender gap in Wikipedia's content, specifically in the representation of women in biographies, is well-known but has been difficult to measure. Furthermore the impacts of efforts to address this gender gap have received little attention. To investigate we utilise Wikidata, the database that feeds Wikipedia, and introduce the "Wikidata Human Gender Indicators" (WHGI), a free and open source, longitudinal, biographical dataset monitoring gender disparities across time, space, culture, occupation and language. Through these lenses we show how the representation of women is changing along 11 dimensions. Validations of WHGI are presented against three exogenous datasets: the world's historical population, "traditional" gender-disparity indices (GDI, GEI, GGGI and SIGI), and occupational gender according to the US Bureau of Labor Statistics. Furthermore, to demonstrate its general use in research, we revisit previously published findings on Wikipedia's gender bias that can be strengthened by WHGI.

Original languageEnglish (US)
Title of host publicationProceedings of the 12th International Symposium on Open Collaboration, OpenSym 2016
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450344517
DOIs
StatePublished - Aug 17 2016
Event12th International Symposium on Open Collaboration, OpenSym 2016 - Berlin, Germany
Duration: Aug 17 2016Aug 19 2016

Publication series

NameProceedings of the 12th International Symposium on Open Collaboration, OpenSym 2016

Other

Other12th International Symposium on Open Collaboration, OpenSym 2016
Country/TerritoryGermany
CityBerlin
Period8/17/168/19/16

Keywords

  • Biographical Database
  • Gender Disparities
  • Wikidata
  • Wikipedia

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