Beyond the stars (of rating)
My friend Jon Sykes at the Glasgow Caledonian University eMotion Games Lab sent me this link to a talk at TED. Like most TED talks, this one’s intensely interesting, but that’s not the point here. Take a look at the how the video is rated; it’s essentially a bounded tagging system. Jon thinks this might be useful for Wikiup, since it’s more informative (creates a tagging cloud to generate a more qualitative rating than a star system).
Certainly folksonomic tagging has been in my head for a long while now. But honestly, I’m not sure about this for ratings, since the Wikiup system by definition needs to be able to tease out quantitatively “best” versions within certain bounds. But I like the idea that the rating system could be multi-dimensional. Any thoughts world?
what i like about the TED system, is that it delivers both quant and qual… you have three points to share between the multiple reference words. You could give all of your points to a single word, or share them amongst three different words.
So, thinking about rating 3D models, it might score highly for its creativity, but poorly on the technical implementation. This is much more informative than an average rating of 3 (out of 5).
Good point, I focused on the taxonomy and probably underrated the importance of the three points system. I think that we can certainly utilize multi-dimensional ratings, and perhaps a similar points system. Still, it would be useful to ponder a bit on exactly how that works in the Wikiup context. It’s fairly obvious how points affects TED’s tag cloud. I’m less sure how we’d implement that here.