Wikigender: A Machine Learning Model to Detect Gender Bias in Wikipedia

• URL: http://arxiv.org/abs/2211.07520v1
• Date: Mon, 14 Nov 2022 16:49:09 GMT
• Title: Wikigender: A Machine Learning Model to Detect Gender Bias in Wikipedia
• Authors: Natalie Bol\'on Brun, Sofia Kypraiou, Natalia Gull\'on Alt\'es, Irene Petlacalco Barrios
• Abstract summary: We use a machine learning model to prove that there is a difference in how women and men are portrayed on Wikipedia. Using only adjectives as input to the model, we show that the adjectives used to portray women have a higher subjectivity than the ones used to describe men.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The way Wikipedia's contributors think can influence how they describe individuals resulting in a bias based on gender. We use a machine learning model to prove that there is a difference in how women and men are portrayed on Wikipedia. Additionally, we use the results of the model to obtain which words create bias in the overview of the biographies of the English Wikipedia. Using only adjectives as input to the model, we show that the adjectives used to portray women have a higher subjectivity than the ones used to describe men. Extracting topics from the overview using nouns and adjectives as input to the model, we obtain that women are related to family while men are related to business and sports.

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