Slashdot Mirror
Researchers Developing An Algorithm That Can Detect Internet Trolls
An anonymous reader writes Researchers at Cornell University claim to be able to identify a forum or comment-thread troll within the first ten posts after the user joins with more than 80% accuracy, leading the way to the possibility of methods to automatically ban persistently anti-social posters. The study observed 10,000 new users at cnn.com, breitbart.com and ign.com, and characterizes an FBU (Future Banned User) as entering a new community with below-average literacy or communications skill, and that the low standard is likely to drop shortly before a permanent ban. It also observes that higher rates of community intolerance are likely to foster the anti-social behavior and speed the ban.
It is stupid to me because it does not solve a problem. Detecting trolls is certainly not a problem, dealing with them is. They need to work on algorithm for that.
The original paper doesn't seem to be about automatic banning at all; that seems to have been added to the headline and the article linked to here (and therefore the summary). The paper says this: "automatic, early identification of users who are likely to be banned in the future."
While that identification could be used for automatic banning, I think it would be more likely to be used to flag potential problem users, which could be very useful in determining which reported posts to investigate first rather than dealing with all of the "I don't like this post so I'm reporting it" instances.