Women Are 'Eye Candy,' Not News Sources, Online
The world just got some pretty strong evidence that online news is sexist.
While it won’t shock anyone to learn that Y chromosomes are overrepresented in news coverage, a new study found that women are more likely to appear in photographs than in the text of news stories.
Researchers in the United Kingdom used artificial intelligence software to catalogue an enormous corpus of English-language news on the Internet. They vacuumed up 2.3 million articles published by 950 online news sources, from the BBC to the New York Post, over six months from October 2014 to April 2015.
They used AI programs to search for faces in the articles’ lead images and categorize them by gender. Names in the text of news sources or subjects were also sorted by gender. “The proportion of females was consistently higher in images than in text, for virtually all topics and news outlets,” the researchers wrote in the article published in the journal PLOS ONE by researchers from the University of Bristol and Cardiff University.
The idea that news disproportionately focuses on men has been studied for years. Other researchers have pointed out that the imbalance in coverage reflects underlying inequalities in society: If leaders in government and business are disproportionately male, for example, the journalism about those subjects will reflect that. (They are, and it does.)
Women are better represented on some beats—fashion, in particular, was the only topic where women were more likely than men to be mentioned in the text and featured in photos. That’s hardly a feminist victory. In sports stories, more than 90 percent of the subjects named or people quoted were men.
But skewed gender balance in the subject matter doesn’t explain why women are more likely to show up in photographs than text. The authors say their findings provide evidence for a longstanding feminist critique: "When women do show up in the news, it is often as 'eye candy,’ thus reinforcing women's value as sources of visual pleasure rather than residing in the content of their views."
The finding is bound to sadden and infuriate. The authors say that the combination of AI software and a giant sample of articles allows researchers "to gather extensive empirical support, on a scale previously inconceivable, for long-standing claims around the marginalization of women in the news.” The same technology could be used to document "proof of progressive gender representations when and where they occur," they write. In online news, those examples are few and far between.
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