One of my motivations for playing with interfaces to news data is to better understand the relationship between the upstream news creation, selection and propagation process and the downstream news consumption behaviour of the audience (or product).
While the middle classes (in the US at least) are becoming more attentive to where there food comes from and what it is made of (witness how Wholefoods promotion of locally sourced organic produce has forced many other supermarkets to follow suite) the same attention is not given to news.
There are many interesting news aggregators out there (e.g. Google News), but they mostly play the same role (and give the same results) as editors of the front page. It is unlikely that the Google News front page doesn't show pretty much the same major stories as the BBC front page, for example. In addition, they are tied to the decision process encoded in the data that they mine to determine the selection of articles for promotion.
The d8taplex news page sticks with the timeline of the news being generated, clusters similar news content (with a more longitudinal view of the story than most aggregators) and ties in the bit.ly statistics to indicate what users are clicking on (via sharing the bit.ly links via twitter, etc.).
With this simple interface, I can spot news stories of interest to readers but which aren't being broadly passed around by the news outlets being crawled (e.g. the recent earthquake in Japan had almost no coverage but got a lot of clicks). In addition, I can see news articles which are getting a lot of attention from the agencies but with less engagement from readers (e.g. the Pope's visit to Africa).
Eventually, I'm hoping to arrive at an interface that will allow users to both select news of interest, but also be aware of the tyranny of preferential attachment.