A Twitter idea that I want to make sure gets archived somewhere so that I can build it later: it would be really cool if, as a reader and news consumer, I could indicate graf by graf on an article whether “I already knew that” information or “this is news to me.” For someone reading a lot of the #swineflu coverage, it seems as though most of the articles are largely rehashed information that I’ve seen elsewhere. Empowering the user to give feedback as to whether they’ve heard the information before will allow the news organization to focus more on providing new and unique coverage.
This data generated by ranking the freshness of information would immediately begin to build profiles of what the reader knows. If they’re logged in, the news organization could put this information on what they’re indicating they know and don’t know in a database, start aggregating it, and then feed the reader related links and stories on similar topics. Related information, however, would now be determined by both topical metadata and a virtual profile of their knowledge base. On the front end, the data that the readership is contributing could go towards a rating of how “fresh” the article is. If the organization were really forward-thinking, the content of the article could then depend on this profile of how much the reader knew.
Voilà. Another new format for news.
2 Comments
I think this is a dope idea. My managing ed had this @ off my retweet of your idea: [“@alexismadrigal Why stop at 2? “Good context” “This is irrelevant” “This is incorrect” “This appears to have been written by an alien”]
Would be interesting to develop the right categories to get people clicking. Might give you some insight into what people are reading for, too.