The Escape blog has another idea on how to make Digg a bit less slanted toward the top users: Collaborative filtering. Basically, make it so that you can get a view of articles dugg by people who dugg similar articles to those that you dugg. (I am so sick of the term “dugg” now!)

While this seems similar to the text mining idea I floated earlier, it also has the advantage of bringing up articles which are truly relevant and interesting for an individual user. Since the w

Many sites have already reported on the fact that the popular news site, Digg, is overwhelmingly controlled by a very small group of users. Furthermore, some users predict that unless Digg can again become a true interactive community, the site is done for, because it will become repetitive and untrustworthy; neither the word of the masses nor properly edited and authentic journalistic content.

Many of these complaints have one thing in common: They examine the large quantity of front-page (highly “dugg”) articles which are, in fact, duplicates of previously dugg articles from less well-connected users.

And so, I propose that what Digg could do to “save” itself (as though the wildly popular site truly needs a saviour) is to reduce duplication through textual analysis data mining. Or, less technically, by helping users find related, dugg, articles to the one they’re digging or reading.