Over at the P2P Foundation there’s talk of multi-dimensional rating being used to develop social or community reviews of news stories. The company behind this, NewsTrust – which has been in public beta since November 28, asks reviewers to rate stories on a numerous factors such as:
Recommendation: Is it a good story?
Trust: Do you trust this publication?
Information: Is this story informative?
Fairness: Is this story fair?
Sources: Is this story well sourced?
Context: Does this story show the “big picture”?
They’ve got data that shows aggregated citizen reviews produces results that are as reliable as those produced by professional journalists – thought there are differences (see DownLoad slides. It’s hard to tell if the small differences in rating are statistically significant or whether the citizen submitting reviews are representative of the general public – as the members list is still pretty small (if the public list approximates the actual number of members).
Still by substituting multiple ratings users can quickly and graphically make decisions about news stories that previously could only have come from reading multiple versions of the story or numerous peoples comments on it.
Using rating does other things. It makes participation easier. And from a presentation perspective it also allows you to present this information so it matches users content exploration.
This model shows that even if you don’t own the content (which NewsTrust doesn’t) it’s possible to add value around it if you engage users to create secondary content.
The one suggestion that I’d offer to NewsTrust is to develop a browser plug in that lets users rate stories from any web site as their on it, or to see aggregated reviews when they land on a reviewed page. This would drive participation and value more than “invite a friend” mechanism of social distribution – and extend the NewsTrust social review approach into traditional as well as new media.