After what seemed like endless hints and pre-announcements, social news site Digg will finally start rolling out its "Recommendation Engine" this week. Kevin Rose, writing on the official Digg blog, explains how the new feature takes a user's "past digging activity" to identify "Diggers Like You" and "suggest stories you might like". The problem that Digg is attempting to tackle is that, as the site has grown, it's become increasingly difficult to cut through all of the noise aside from visiting Digg's front page which only displays stories that have garnered a sufficient number of votes (or "diggs"). In particular, the usefulness of the site's "Upcoming" section hasn't scaled now that there are more than 16,000 stories submitted everyday. And in typical Web 2.0 fashion, the more you use Digg, the better recommendations you'll receive, as the "engine" learns more about you. "As you increase your activity on Digg, the Recommendation Engine will get to know you better and will suggest more targeted content and Diggers Like You. You can always remove specific users from the Recommendation Engine by clicking on the user name and selecting ‘remove from Recommendation Engine.’" As I noted in a previous post on Digg's upcoming "Recommendation Engine", over time, advertisers may well also see a payoff as Digg’s users organize themselves into "social networks within the larger social news site’s community":
The result is that the site’s content becomes even more relevant and social to its users, while at the same time providing even more hooks to advertisers.
The isn’t conspiracy theory stuff, it’s just the way any ad-funded site works which feeds off its users’ social graphs. MySpace is refining its data mining and ad-targeting, Facebook has plans to the do the same. We’re now really starting to see phase two of the social networking phenomenon kick-in. Monetization.Watch the video preview of Recommendation Engine embedded below...
Digg Recommendation Engine from Kevin Rose on Vimeo.