Extrapolating strictly from my own browsing behavior while reading the first few on this list, I've noticed that the more interesting I find an article, the more tabs to linked Wikipedia articles I open up for further reading.
Of course, articles with more links are likely to spawn more tabs, so this score would be expressed as a fraction of the total links in the article that were followed.
That's just for starters; none of this considers the actual text of the article. Once you throw in semantics...
EDIT: I generally don't follow links to articles on more well-known topics [e.g. places], but that shouldn't penalize the article. So there needs to be a ranking for well-known-ness, and consider the fraction of followed links to articles that are less well-known.
1) Crawl the entire web
2) Assume that a link to a page means it is interesting in some way
3) Compute the link graph
4) Pages that are pointed to the most are the most interesting
(More advanced versions of this algorithm may implement the following steps: 2a): Discover spamming, 2b) Work out methods to combat it).
(Actually, http://en.wikipedia.org/wiki/HITS_algorithm is probably better because it builds in topic specificity, which allows it to match better match an individuals interests)
