Boffins develop automatic troll slaying

Wikia_HP_-_Mountain_TrollResearchers at Cornell University have come up with a way to identify internet trolls  80 per cent of the time.

The software could create the possibility of creating automated methods to spot and auto-ban forum and comment-thread trolls.

Justin Cheng, Cristian Danescu-Niculescu-Mizil and Jure Leskovec submitted the paper Antisocial Behaviour in Online Discussion Communities [PDF], which details the findings from an 18-month study of banned commenters over three high-traffic communities: news giant cnn.com, political hub breitbart.com and the vocal gaming communities at ign.com.

The study, which was partly-funded by Google and had the cooperation of the Disqus commenting ecosphere, compared anti-social users (‘Future Banned Users’ or FBUs) ‘destined to be permanently banned after joining the community with those joiners who are not permanently banned (Never Banned Users or NBUs) in the study-period.

Most of the study’s findings fell into the blinding obvious category. for example over the 10,000 FBUs studied, nearly all began their commenting life at a lower perceived standard of literacy and  clarity than the median for their host groups, with even that standard dropping in the final stretch towards a moderator ban.

Pre-ban troll posts tend to home in on a smaller number of comment threads relative to the number of posts – the classic characteristic of digging in for a sustained flaming match either with the host community or one or more members of it who have decided to engage the troll.

On CNN, trolls were more likely to initiate new posts or sub-threads, whilst at Breitbart and IGN they were more likely to weigh into existing threads.

However what was interesting was that immediately intolerant communities are more likely to breed trolls:

Users who are excessively censored early in their lives are more likely to exhibit antisocial behaviour later on.While communities appear initially forgiving they become less tolerant of such users the longer they remain in a community. This results in an increased rate at which their posts are deleted, even after controlling for post quality.”

A troll is a semi-literate, provocative and fairly persistent poster, whose descent into totally anti-social behaviour is summoned at inverse speed to that with which the host community rejects them, and whose final posts before a permanent ban are characterised by persistent and heated battle on a small number of topics.

The researchers thing it is a little hard to spot a troll since it system misclassified them one in every five times. #

“While we present effective mechanisms for identifying and potentially weeding antisocial users out of a community, taking extreme action against small infractions can ex- acerbate antisocial behaviour (e.g., unfairness can cause users to write worse), “ the paper said.