Researchers develop Troll-detector

April 20, 2015: Tired of internet trolls witch hunting you? Well, Researchers at Cornell University has a good news. As Guardian reports, US Academics have discovered a common characteristics among website commenters who go on to be labelled trolls.
Researchers belongs to Cornell and Stanford University studies banned commenters in detail on three popular sites CNN, Breitbart and IGN. All of these sites use Disqus as commenting platform. The researchers analysed the posts for over 18 months to reach to some meaningful conclusions that can help us make internet a less noisy place.

Nearly 35m comments from 2m users were examined. Researchers accessed the banned, reported posts. And this is what they wrote in their report: “We find that such users tend to concentrate their efforts in a small number of threads, are more likely to post irrelevantly, and are more successful at garnering responses from other users,” the researchers wrote in a report called “Antisocial Behaviour in Online Discussion Communities”.
“Studying the evolution of these users from the moment they join a community up to when they get banned, we find that not only do they write worse than other users over time, but they also become increasingly less tolerated by the community.” The study was sponsored by Google, which was aimed to compare the anti-social users or Future banned commenters(FBUs) with well-behaved commenters or Never banned Users (NBUs).
From the data, the academics were able to build a statistical model that could predict with 80% accuracy if a given user would eventually be banned, by examining their first five comments. The authors hope the model can be used to target antisocial behaviour earlier and more effectively, reports itp.net.
Source: ITP.net, Image courtesy: Deviant Art


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About Mohammed Rizwan

An Electronics Engineer by education, a part-time blogger by passion. He loves everything about technology, hence he writes about it. Interest includes Technology, Startups and Mobile Applications.
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