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A few weeks ago, Joshua Porter wrote about how Amazon.com improved the way they display a summary of user reviews:

For years Amazon’s interface showed the average review, so viewers could tell the general mood surrounding a book. If it was a 5 star or a 1 star book, then that would be instantly recognizable.

But over time it became clear that the rating system had a fault: if the average rating was somewhere in the middle, say 3.5 stars, it was unclear whether it was just a dull book that most people rated as mediocre or if it was a polarizing book that half the people rated 5 and half the people rated 1. A political book, for example, usually polarizes.

The solution they came up with is a graphic that shows not only the average review, but also the distribution:

I like the new visualization, but I still find that the meaning doesn’t really jump out at me. I have to really concentrate for a few seconds to grok the graphic.

I just ran across another take on this problem. David Abbet points to a much simpler solution:

Instead of using stars, Summize displays color bars which summarize the reviews: the more green, the more positive they are. Where stars only give an average rating, those color bars really add some depth to the information.

I like it. Much easier to understand at first glance, I think. And as swissmiss points out, it’s cool that both their logo and their favicon reflect the style of the color bars.

Anand pointed me to a roundup of cool data visualizations. My favourite of the bunch is Elastic Lists:

Elastic lists are a technique for browsing multi-faceted data structures. A multi-faceted data structure is one that is structured by several different attributes — in this example, Nobel Prize winners are grouped by the area (physics, chemistry, etc.), nationality and gender of the winner, and year. What I really like about this visualization is how the relative weights of each of the metadata values are represented by the size of the box. You can see in the image above that the box for male is much bigger than the box for female, indicating that there have been more male winners of the Nobel Prize in physics.

The technique is similar to the now-ubiquitous tag cloud (an example from Flickr above), but I like the approach from Elastic Lists better, because it’s more subtle. I find that some tag clouds tend to punch you in the face with the main terms, but this approach gives the words themselves equal footing, while still providing some useful secondary information.