Wired Interview: "REDDIT’S ‘MANOSPHERE’ AND THE CHALLENGE OF QUANTIFYING HATE"

I was interviewed alongside many other great researchers for this WIRED article that discusses the ups and downs of doing research about the many growing communities of online misogynists. You should check it out: https://www.wired.com/story/misogyny-reddit-research/

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Misogyny online is more felt than understood. A growing cohort of researchers—many of them women—are attempting to change that. Since Gamergate and the Toronto attack in particular, they’ve spent thousands of hours spelunking through these subreddits, trying to find meaning in the misogyny. A recent paper, “Exploring Misogyny Across the Manosphere in Reddit,” attempts something few others have: mining the entire space like one vast linguistic database to find patterns in the way hate has evolved online. According to other researchers, the data, based on 6 million posts made over seven years, will be crucial to the field.

Maybe you have a morbid fascination with the internet’s squalid underbelly and instinctively knew this. (I do, and did.) “If you’re paying attention to the rise of misogyny online, a study like this might not teach you anything you don’t already know,” says Emma Vossen, a researcher who studies gaming and online culture at York University. “That’s not negative. For me and a lot of other people like me, it’s important to have these studies.” Most work on the subject, including Vossen’s, has been highly qualitative, hinging on one or several researchers’ lived experiences within a community.

Farrell’s study, by contrast, is unusually quantitative. Coauthor Miriam Fernandez, a senior research fellow at the Knowledge Media Institute, applied natural language processing to subreddits’ entire lifetime of posts, categorizing their language into nine categories of misogynistic language already described by existing feminist scholarship: physical violence, sexual violence, belittling, patriarchy, flipping the narrative, hostility, stoicism, racism, and homophobia. The patterns of increasing violence and hate are algorithmically detected rather than personally observed, which helps shut down skeptics. “This isn’t just something a feminist is saying online,” Vosesen says. “These numbers can’t be dismissed. This big picture data can back up small microanalyses I and others find most valuable: ‘Here’s the macro perspective, now let me talk about this specific r/KotakuInAction thread that’s talking about how much I suck.’”