If You Care About Women, You Should Edit Wikipedia Differently

Although controversies over gender and Wikipedia have been in the news recently, a current study, It’s a Man’s Wikipedia? Assessing Gender Inequality in an Online Encyclopedia, using computational linguistics takes on gender bias in the encyclopedia as a whole. A team of researchers from Germany and Switzerland concluded

“while women on Wikipedia are covered and featured well in many Wikipedia language editions, the way women are portrayed starkly differs from the way men are portrayed.”

After conducing computational analysis of entries on notable men and women in six language versions of Wikipedia, the researchers found disparities in two of the four metrics they used to assess potential gender inequalities. Coverage bias, probably the most familiar to followers of Wikipedia, simply tallies the number of pages dedicated to women as compared to those written about men. Structural bias refers to linkages within the Wikipedia architecture to and from pages about women and men. Lexical bias focuses on language used on pages about individual women and men. Finally, visibility bias counted the number of articles about women and men that made it to the coveted “front page” spot on Wikipedia.

First, the good news. In terms of pages based on notable individuals, women are doing pretty well in Wikipedia at least in comparison to other dataset. The researchers compared Wikipedia to three external databases of notable persons.  Wikipedia came out the clear winner in terms of content devoted to women. In fact, women are over-represented in Wikipedia compared to these other sources.  Similarly, in terms of visibility, there appears to be no bias precluding entries about women from being highlighted on the front page.


Table 1: English Gender-Specific Likelihood Ratios, from Wagner et al.
Table 1: English Gender-Specific Likelihood Ratios, from Wagner et al.


Figure 6: Lexical Bias from Wagner et al, Is It a Man's Wikipedia?
Figure 6: Lexical Bias from Wagner et al, Is It a Man’s Wikipedia?


Unfortunately, women did not fare so well in the other two measures of potential bias. In terms of structural bias, the researchers uncovered two disturbing trends.  “Articles about people with the same gender tend to link to each other” and “articles about women tend to link more to articles about men than the opposite.” In addition, articles about women tended to over-emphasize the subject’s sex (figure 1). Women’s pages were more likely to contain words like “woman,” “female,” or “lady,” but men’s pages were less likely to contain “man,” “masculine,” or “gentleman.” Furthermore, women’s relationship status also appeared more frequently via words like  “married,” “divorced,” “children,” or “family.” (figure 2)

Disappointingly, the English language version of Wikipedia (along with the Russian) showed the strongest bias in both these areas.   So what can we do about this?

While the efforts of the Wikipedia community to cover women appear fruitful, our results highlight that editors need to pay attention to the ways women are portrayed on Wikipedia. 

For the past two years, I’ve organized a virtual Wikipedia edit-a-thon. As opposed to the face to face edit-a-thons which often have the admirable goal of entering more content about women in to Wikipedia, particularly through the authoring of new articles in specific areas such as art or STEM, such endeavors may be daunting to the less experienced editor.  I have focused on smaller edits, and two of these methods seem well-suited to addressing the structural and lexical biases revealed by the latest study.

  1. De-gender women’s pages which means not only inserting gender-neutral words, but also excising extraneous content that refers to the subject’s sex that isn’t necessary and to her familial status (wife, mother) if not related to her notability.
  2. Insert links to women’s pages While less glamorous and fun than authoring a new article, inserting links emphasize the importance of women rather than isolating them on their own pages. Make sure to add links to women’s pages from pages about men as well as women.

In addition to these suggestions, which directly address the study’s findings, two other editing techniques I have used successfully would also help ameliorate these biases.


  1. Add men’s mothers. My foray into editing Wikipedia began when I realized that many famous men’s mothers and wives did not appear in their entries, while their fathers did. If family information is present in an entry, add women, mothers, wives, daughters, alongside patriarchal family references to the entries of famous men.
  2. Improve the quality of articles about women. One metric that the current study did not use is the quality of articles about women. The WikiProject Women’s History group has done an excellent job compiling these statistics. (figure 3)  Improving existing articles is not only an easier task than writing a new one, but an invaluable one in ensuring that entries about women are not deleted due to poor quality.


Women’s History articles by quality and importance, from Wikipedia: WikiProject Women’s History/Assessment
Women’s History articles by quality and importance, from Wikipedia: WikiProject Women’s History/Assessment


This year’s virtual edit-a-thon to Write Women Back into History is taking place during the week of March 9-15. Participants edit in the location of their choosing and at the convenience of their individual schedules. I provide helpful videos, links to potential pages for editing, virtual support, and suggestions for pedagogical strategies.  Sign up here.


  1. Victoria

    I think that excising content should be done carefully. I use family information provided by Wikipedia when trying to trace copyright holders. Whether an artist, designer, or maker was married or had children might not impact that individual’s creativity or art practice or notability but it is incredibly useful information for me as a user. It might be more useful to include family information to men’s entries rather than delete it from women’s.

  2. Michelle Moravec

    Hi, Thanks for the comment. I’m sorry if I wasn’t clear, but I was advocating precisely that in #3, although I only do this if family information is already present or in some way relevant. To clarify #1, the study authors noted gendered or familial terms used disproportionately to refer to female subjects of Wikipedia articles. The recommendation is to remove those references, not the information about the subject’s relatives. Hope that helps! Happy editing.

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