It's a similar measure that's often used in NLP. Sentences, documents etc. are usually stripped of common or popular terms first and the remaining ones tend to have higher information value. It's not entirely a surprise that it works for meta-language constructs like the web and site popularity.
1) I am basically certain that it doesn't work. Imagine something this simple actually did work in general. Do you think Google, Bing, etc, wouldn't have implemented it?
2) I think the analogy is extremely flawed. nytimes.com is by no means a web page equivalent to "the" or "a" in language. Articles, pronouns, etc, don't really carry meaning. Despite being popular, nytimes certainly does.