Visual Gender Biases in Wikipedia: A Systematic Evaluation across the Ten Most Spoken Languages

Authors

  • Pablo Beytía Humboldt University of Berlin
  • Pushkal Agarwal Kings College London
  • Miriam Redi Wikimedia Foundation King’s College London
  • Vivek K. Singh Rutgers University Massachusetts Institute of Technology

DOI:

https://doi.org/10.1609/icwsm.v16i1.19271

Keywords:

Ranking/relevance of social media content and users, Credibility of online content, Qualitative and quantitative studies of social media

Abstract

Wikipedia, a collaborative crowd-sourced platform, is the largest, most visited online encyclopedia. Since it spreads information freely in more than 300 languages, many users, tools, and dashboards rely on its content. Hence, there is a need to maintain its fairness and completeness. However, previous research has indicated the existence of a significant gender gap in Wikipedia biographical articles. We already know that a minimal proportion of those articles portray women and there are gender asymmetries in the textual content of these articles, but little has been reported about the visual aspects (e.g., image volume or image quality) of the gender gap. Here, we analyze all biographies available on Wikipedia across 300 occupations in the ten most widely spoken languages, and undertake quantitative and qualitative analysis of gender differences in the written and visual content. The cross-lingual results indicate that (1) much of the male bias in content arises when editors select which personalities should have a Wikipedia page, (2) the trends in written and visual content are quite dissimilar, (3) men biographies tend to have more images across languages, and (4) female biographies average better visual quality. A more granular analysis is performed on English Wikipedia, distinguishing trends in occupations and qualitatively analyzing science and technology biographies. The overall results shed light on the kinds of visual biases that emerge in the collaborative creation of Wikipedia and yield guidelines for future management of contributions on the platform.

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Published

2022-05-31

How to Cite

Beytía, P., Agarwal, P., Redi, M., & Singh, V. K. (2022). Visual Gender Biases in Wikipedia: A Systematic Evaluation across the Ten Most Spoken Languages. Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 43-54. https://doi.org/10.1609/icwsm.v16i1.19271