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Gender and country biases in Wikipedia citations to scholarly publications

Xiang Zheng, Jiajing Chen, Erjia Yan and Chaoqun Ni

Journal of the Association for Information Science & Technology, 2023, vol. 74, issue 2, 219-233

Abstract: Ensuring Wikipedia cites scholarly publications based on quality and relevancy without biases is critical to credible and fair knowledge dissemination. We investigate gender‐ and country‐based biases in Wikipedia citation practices using linked data from the Web of Science and a Wikipedia citation dataset. Using coarsened exact matching, we show that publications by women are cited less by Wikipedia than expected, and publications by women are less likely to be cited than those by men. Scholarly publications by authors affiliated with non‐Anglosphere countries are also disadvantaged in getting cited by Wikipedia, compared with those by authors affiliated with Anglosphere countries. The level of gender‐ or country‐based inequalities varies by research field, and the gender‐country intersectional bias is prominent in math‐intensive STEM fields. To ensure the credibility and equality of knowledge presentation, Wikipedia should consider strategies and guidelines to cite scholarly publications independent of the gender and country of authors.

Date: 2023
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https://doi.org/10.1002/asi.24723

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