DiggStatus: Digging Deep Into Digg Users' Statistics

• It needed to chronicle the Digg Effect. This has been done many times before, so I needed to come up with something that would provide more information than a typical traffic chart.
• I wanted to know more about the Digg community, and how most people use the site. There has been plenty of coverage of the Top Users, but nothing that really shows their stats in the context of the entire Digg user base.
• It needed to determine profitability of "blog spamming" by tracking the ad revenue of one Google AdSense advertisement while being linked to on the Digg.com front page. We have all seen people post a summary of a news story on their ad-invested blog and post the link to Digg. I wanted to find out how much they were making by doing this.
• Most importantly, it needed to make it to the Digg front page.

I decided the best way to accomplish all of these tasks would be to create a tool that would allow Digg users to see how their usage stats (submissions, stories dugg, stories commented on, etc) stacked up against their peers. The tool would share information with visitors as it learns more and more about the community.

First, I had to build an web application that would scrape and cache user statistics from Digg. The stats had to be cached in a local database for two (fairly obvious) reasons: 1.) I needed to have all of the stats available for every new query to be able to compute membership-wide averages, and 2.) because I didn't want to ping Digg more than once for any given user. Once the app was complete, it needed glue. It needed a quality that would guarantee the tool a spot on Digg's front page. Yes, statistics are nice and it's cool to see how your usage stats compare to the rest of the site's members, but the average user probably won't find a bunch of numbers very intriguing.

I decided to display the users' stats and their comparison to the rest of Digg users' stats without showing a single number on the page. Instead, I showed colored bars that scaled to match a user's deviation from the site's average statistic for each of 11 categories, and added a short note that poked fun at the user for being at that position relative to the average. The notes were intended to match a common attitude among Digg comment threads. No matter what, the user would get hazed. This aspect of the interface triggered an emotional reaction from the user, which is more than you can invoke with a chart and numbers.

:: Page 1: Introduction
Page 2: Submission/Promotion Graph