TY - GEN
T1 - Monitoring the gender gap with Wikidata human gender indicators
AU - Klein, Maximilian
AU - Gupta, Harsh
AU - Rai, Vivek
AU - Konieczny, Piotr
AU - Zhu, Haiyi
PY - 2016/8/17
Y1 - 2016/8/17
N2 - 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.
AB - 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.
KW - Biographical Database
KW - Gender Disparities
KW - Wikidata
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=85006744612&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006744612&partnerID=8YFLogxK
U2 - 10.1145/2957792.2957798
DO - 10.1145/2957792.2957798
M3 - Conference contribution
AN - SCOPUS:85006744612
T3 - Proceedings of the 12th International Symposium on Open Collaboration, OpenSym 2016
BT - Proceedings of the 12th International Symposium on Open Collaboration, OpenSym 2016
PB - Association for Computing Machinery, Inc
T2 - 12th International Symposium on Open Collaboration, OpenSym 2016
Y2 - 17 August 2016 through 19 August 2016
ER -
