I'd love to hear your feedback.
When a campaign is created it queries Twitter's API for the brand name (e.g. "Hipmunk") every 10 minutes, and then runs filters on each tweet to categorise it.
I guess you could add some mobile notification mechanism, but I already love the product as it is right now.
As far as I am concerned, you might as well charge twenty bucks a month for it. It's a great product.
Hope you enjoy the feedback.
Just a little note. In your demo one of the negatives is misclassified which shouldnt really happen in a demo :P
It's kind of sad that the two comments asking about how this works under the hood are at the bottom. A bag-of-words model -- any n-gram model, by extension -- is an entry-level approach: it has decent performance but won't win any awards for how it handles complex language structures (and you'd be surprised at how complex 140 characters can be). Hence most commenters are praising the UI.
Good luck moving forward with this. If your model learns to handle negation intelligently or starts to use morpho-syntactic features, I'd be glad to chat with you.