Inarticle.org is an analysis tool for news stories or any other online writing designed by Jeremy Scott Diamond, a grad student at NYU's Interactive Telecommunications Program. Using his own custom programming and APIs, InArticle parses through text and highlights key words, proper names, places, phrases, and quotations and creates visually pleasing graphs based on the data.
Positive/Negative analysis of different articles on the same topic:
In additional to offering recent top headlines from Google News feed, it's also possible to plug in your own links to compare. I tested this out using articles from the New York Post and the Toronto Star about last night's basball game (Yankees lost to the Blue Jays 8-1).
Somehow, the Post managed to keep the article 34% postive (in blue), even though its team lost. A little New York attitude, eh?
While InArticle's graphs are elegant and look visually fantastic, I'm wasn't sure how actually useful this would be, or who would actually use it to analyze news. So I rolled my chair across the office to show it to BuzzFeed Politics writer McKay Coppins to get some insight into what someone who consumes news for more than just cat videos would think of the site.
While Coppins agreed it looked cool as heck, he had reservations about how this would actually be used:
"From a politics standpoint, I can easily see this being used as a tool to call out alleged media bias," Coppins said. "These days, it feels like half of the political conversation revolves around how various outlets are slanting their coverage of a given story, rather than the news itself."
"As a journalist, I'm not sure how accurate the site would be in that regard. Can an algorithm based on keywords really figure out the tone and intent of a story? Most of the time, humans aren't even very good at that."