JuLiA Public Demo Is Live

JuLiA is a comment moderation system for online publishers. She uses machine learning and natural language processing techniques to recognize abusiveness in blog comments. The idea is that online publishers can use her to automatically publish or delete these comments based on the amount of abusiveness she has identified.

Currently most online publishers use a combination of keyword filters, a staff of human moderators, and feedback from their own community in order to moderate incoming comments. There are problems with every one of these methods, and we (modestly) think we can do it a whole lot better.

Keyword filters especially are easy to trick. All you have to do is b r e a k u p a w o r d, repl@ce a letter with a symbol or num8er, or get creative with your insults, and you can get some pretty foul content past them.

When it comes to human moderators, bias and laziness (not to mention cost) tend to be really big problems, but even good moderators are fallible to a point. It’s really difficult to stay neutral when your job is to read through hundreds, maybe even thousands of reactionary, racist, threatening, stupid, nasty, and heinous comments every day. Even the best and most consistent moderators are given a Herculean challenge. Basically, online publications with user-generated content are the Aegean stables and human moderators are the ones who have to shovel that shit. I know how hard it is because in order to train JuLiA, I wind up tagging and auditing thousands of these nasty comments every week. It makes you doubt humanity, I swear.

And finally, there’s the community. Hmm…what to say about that? Relying on the mob to moderate itself is kind of a craps shoot, and you can see vastly different results when you look at different websites. To a certain extent, the success of this strategy relies on the kind of user your content is going to attract. For example, the comments section on USA Today is absolutely overrun with trolls. On the other hand, The Daily Kos has achieved some pretty decent results with their labyrinthine community moderation scheme, but that’s partially because their users are a bit savvier to begin with.

But there is a deeper problem with community self-moderation, and that is the fact that the users tend to form biased cliques, and eventually this bias becomes institutionalized. On The Daily Kos for example, you might be able to say something really nasty and offensive, and it will get through as long as you are attacking a group or an individual that their moderators hate as well. And the reverse situation is even worse…if you say something at all critical of a group or individual that their moderators love, then it is subject to censorship even if it contains no abusive language. The community moderation system on Slashdot is another famous example of this phenomenon.

So the basic jist is that all of the current methods have some serious limitations, and even when they are used in combination, a lot of abusive comments get by every day. This is a big problem for publications, because it reflects poorly on the publication as well as the community. Our demo lets you see a slice of the abusive content that gets by all these systems on a daily basis. We want to demonstrate the fact that JuLiA, unlike everything else out there, actually catches this stuff. And when you see the kind of stuff she’s catching, it’s actually sort of surprising to discover some of the truly awful things making it through the editors at these supposedly “respectable” publications.

So check it out...