Digg unveils data visualization finalists, Apollo in the house
Digg's got some new eye candy. Go vote for it over at Diggcontest.com
The Webware 100 is going strong, and if you're still in the voting mood, Digg has unveiled their list of 10 finalists for their API visualization contest, which can be voted on by--you guessed it--digging. Like Digg Expose, which I wrote about earlier this week (and is coincidentally a nominee), each of the finalists has found some really neat ways to play with Digg user data.
One of the most interesting aspects of this contest is the use of Adobe Apollo. Four of the 10 finalists' offerings are served up as Apollo apps, which is fairly impressive considering how young the platform is. The only downer is having to download and install them as applications.
Currently, one of the most popular visualizations is DiggCity, which represents the 10 most recently popular stories as buildings in a small, virtual city. Users who Digg stories are displayed as stick figures, who go into each building and make it bigger. It immediately reminded me of Ghostbusters for the Atari 2600 with its simplistic graphics style, and meandering residents (see picture to the right), but succeeds in quickly showing you which stories are getting the most growth.
Another neat nominee is WordWeb, which joins together the most prevalent keywords used on the service to show relationships. Stories with similar keywords get grouped and linked up, and you can simply click on keywords to explore what other stories are connected. Exploring WordWeb feels a little bit like Quintura, the visual search engine, although the only results you're getting will be Digg stories.
My personal favorite of all of the entries is DiggCharts, which is a really simple tool to track popular stories, and when they got there. Typically this information is relegated to the content owners who have access to traffic stats; in this case, you're getting the data from when the story made its way onto Digg. Digg Charts breaks down the popularity of the 10 stories that most recently made their way onto the front page. You can then drill down through each story and view when the story began to pick up its Diggs, user comments, and popularity. In many cases, the curves all have a similar flow, although I came across one or two that had gone up and down a few times before beginning to peak.