Some attempts at making long running news stories explorable and discoverable based on a users interests.
When an event has been going on for an extended period of time it can be overwhelming to keep up with whats going on. You might want every minute detail of the history or politics of the region, or you might be more interested with the human stories of those affected.
Current news websites require you to either spend an extensive amount of time searching or happen to get lucky and find a relevant article as it makes its way across the "front pages".
nooz is an ongoing experiment to see how articles can be discovered and related content explored by matching content to a users interests.
Most mainstream publications have a relativly "flat" model of producing content. Seemingly this relates back to how old fashioned news papers were produced. There is a series of boxes which require filling, and correlation and linking is the responsibility of the reader. Rough categorizations might "tag" the content but this only marginally improves discoverability.
Is this the best we can do?
By moving to graphical models where articles are nodes which can be connected by various types of edge we can allow a user to explore content based on their interest in a general field (say, politics) or their particular interest with a given topic.
