How much would, say, the New York Times have to pay to have the entirety of its newspaper analyzed and annotated every day?
The question is not hypothetical.
The librarians could go home, and fancy machine learning and natural language processing could step in and start extracting entities and tagging content. Hi, did you know Bill Clinton is William Jefferson Clinton but not Senator Clinton?! Hey there, eh, did you know that Harlem is in New York City?! Oh, ya, did you know that Republicans and Democrats are politicians, who are the silly people running around playing something called politics?!
Twine could tell you all that. Well, they say they can, but they won’t invite me to their private party! And maybe the librarians wouldn’t have to go home. Maybe they could monitor (weave?) the Twine and help it out when it falls down (frays?).
I want to buy Twine’s smarts, its fun tags. I’d pay a heckuva lot for really precociously smart annotation! They say, after all, that it will be an open platfrom from which we can all export our data. Just, please, bloat out all my content with as much metadata as you can smartly muster! Por favor, sir! You are my tagging engine—now get running!
What if Twine could tag all the news that’s fit to read? It would be a fun newspaper. Maybe I’d subscribe to all the little bits of content tagged both “Barack Obama” and “president.” Or maybe I’d subscribe to all the local blog posts and newspaper articles and videos tagged “Harlem” and “restaurant”—but only if those bits of content were already enjoyed by one of my two hundred closest friends in the world.
I’d need a really smart and intuitive interface to make sense of this new way of approaching the news. Some online form of newsprint just wouldn’t cut it. I’d need a news graph, for sure.
See TechCrunch’s write-up, Read/Write Web’s, and Nick Carr’s too.
PS. Or I’ll just build my own tagging engine. It’ll probably be better because I can specifically build it to reflect the nature of news.
