Oneitiscel
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Detecting incel misogyny on Reddit
Dominic Forest and Camille Demers have taught computers to automatically recognize when men's posts on the popular social-media platform target women.
nouvelles.umontreal.ca
On Nov. 7, 2017, the American social-media platform Reddit shut down r/Incels, an online forum with more than 40,000 members. This was in line with a new policy the company brought in, banning content that incites violence.
Deprived of their outlet, where did all those misogynistic incels go? Where online did they wind up conversing, and, importantly, could their conversations still be detected on Reddit itself?
To answer those questions, Canadian researchers at Université de Montréal sifted through reams of posts, applying advanced automated text analysis techniques to distinguish incel comments from other online discussions.
The problem for researchers who study their online presence, however, is that it's hard for computer algorithms to detect incel rhetoric because it uses coded language and is constantly reinventing itself.
That's where the new study — authored by Dominic Forest, a professor in UdeM's School of Library and Information Sciences (known by the acronym EBSI), and his doctoral student Camille Demers — comes in.
Their research began in an EBSI classroom in the fall of 2021. Having participated in international competitions on detecting cyberbullying, Forest suggested that his data-mining students tackle the topic, too.
How do you train a machine to recognize incel discourse? The first step is to feed it a slew of examples. But instead of manually labelling tens of thousands of comments, the researchers opted for a “community bags” approach.
That is, rather than evaluating each message in a Reddit forum (known as “subreddits”), they classified entire subreddits as representative of a specific type of discourse.
Drawing on previous work, they identified 23 subreddits as incel strongholds.
They then extracted 40,000 comments from these forums and labeled them “incel,” and compiled an equivalent sample of comments from more than 13,000 other subreddits to create another corpus tagged “non-incel.”
Incel statements make up only a tiny proportion of online conversations, so an algorithm trained on a realistic sampling of online comments could become “lazy” and identify no comments as incel.
To prevent the computer from taking the easy way out, the researchers trained it on data in which incel comments were overrepresented. They ran a series of tests, varying the proportion of incel comments from 10 to 90 per cent.
Data collection was another headache. As access to Reddit data changed during the project, the researchers turned to compressed archives made available by an online community of enthusiasts.
Well that is nice....
But what was the point in even creating something like this? Reddit's TOS already guarantees that anything that even remotely resembling blackpill content is swiftly nuked, along with the users who engage in it.
Personally, I think their time and effort would had been spent a lot more efficiently if they had decided to create a computer which sniffs out misandrist content instead. Hateful rhetoric which is actually given a blind eye to proliferate. But that is just my opinion....





