On Wikipedia’s recent 20th birthday, the online encyclopedia was widely praised for its success in spreading reliable information about political events. Wikipedia is one of the few socially driven websites where, even though anyone can contribute information about breaking news, misinformation is largely suppressed. And Wikipedia’s coverage of current events often directs attention to its pages about ideas in political science, giving readers context for the news.

But while Wikipedia has developed an impressive record of political and ideological neutrality, it has serious biases in its coverage. From the gender gap in its biographies of scientists to its disproportionate focus on politicians from wealthy countries, Wikipedia’s coverage of people is particularly skewed. And these biases are rampant on the pages that people visit to understand political events.

But because anyone can become a Wikipedia editor, these biases can be corrected. I spent a year working on adding more accurate information on political science. Here’s what I learned.

After major events, readership spikes for biased pages

After major political events, page view statistics show that many readers navigate from Wikipedia’s coverage of the news to more fundamental pages about related topics in political science. One such surge occurred on the day of the 2020 general election, when views of Wikipedia’s U.S. electoral college article rocketed from its typical range of a few thousand daily up to nearly 5 million visits in a day. Such articles’ credibility is bolstered by the fact that Wikipedia articles are built on citations, with every claim attributed to a reliable source. But of more than a dozen academic works cited on the electoral college page, only one has a woman as its first author.

On broad topics like “democracy,” Wikipedia explicitly suggests academic papers or books for further reading. Its academic pages often see surges in attention during major events, as the page on democracy did during the riot at the U.S. Capitol. But among the supplementary works suggested on that page, fewer than 10 percent have a woman as first author. I found a similarly low proportion on the pages for conservatism (11 percent), socialism (3 percent), and dictatorship (zero). These are not exceptions: Even the first authors of the 27 academic works cited on the page for political science itself, in late 2020, included 26 men and one woman.

These disparities matter. For almost as long as Wikipedia has existed, critics have argued that these biases shape its pages’ contents, limiting and slanting coverage that is now viewed nearly 10 billion times each month. Groups that are underrepresented in academia tend to be missing at an even higher rate on Wikipedia. And there is growing evidence that Wikipedia articles have tangible effects, including the power to influence the contents of scientific papers. Wikipedia does not just passively reflect biases. It amplifies and reinforces them.

Citations are only part of the problem

Anyone who tries to learn about the people who research politics will find similar distortions. Fewer than 19 percent of the biographies on Wikipedia are about women, and biographies of political scientists are no exception. Of more than 3,000 biographies of political scientists on Wikipedia, fewer than 700, or only about 20 percent, feature women. This is about 10 percentage points lower than an estimate — now a decade old — that women make up about 30 percent of U.S. full-time political scientists. Similarly, almost half (44 percent) of the political scientists with a Wikipedia biography are American.

Though it’s not clear how many of the world’s political scientists are American, it is hard to imagine that there are nearly as many political scientists in the United States as in the rest of the world put together. And several countries have not a single political scientist represented in a Wikipedia biography.

To try to reduce these biases, every day of 2020, I created or expanded a political-science-related Wikipedia article, writing new pages about political scientists from groups underrepresented on Wikipedia. I was building on almost a decade of work by activists who have tried to correct the gender ratio in Wikipedia’s pages about scientists. This group argues that when such a disproportionate number of the scientists on Wikipedia are White men from wealthy countries, it discourages other potential scientists and reinforces exclusionary patterns in STEM workplaces. Groups aiming to better represent women in endeavors like journalism and the arts have undertaken similar efforts.

Social scientists have been largely absent from this effort. But pages about social scientists have just as much bias as that on STEM researchers, and that bias is likely to do just as much damage.

My year of daily contributions included 264 new pages about women and the first page about a political scientist from each of seven countries. But that increased the proportion of political scientist biographies about women by only about 5 percent, and it only slightly expanded Wikipedia’s coverage of political scientists outside the United States. I also barely improved the citations on existing pages about political ideas. Wikipedia has tens of thousands of political-science-related articles, viewed millions of times each year. Individual efforts can go only so far.

Creating and editing Wikipedia pages can reduce this bias

Bias on Wikipedia is a massive and systemic problem that has accumulated over its two decades, as thousands of volunteer editors have built its base of knowledge. Wikipedia demands that all entries cite independent, reliable sources. As a result, its biases often reflect biases in the world it describes or biases in the information that Wikipedia is built on.

Any political scientist with a book to recommend may wish to keep in mind that anyone can edit Wikipedia. If a few dozen people each added a few well-chosen references, they could seriously reduce biases in Wikipedia’s coverage of major political ideas.

Samuel Baltz (@SamuelBaltz) is a PhD candidate in political science and scientific computing and an MS student in applied mathematics at the University of Michigan.