I'm working a presentation that includes the concept of search as social media, both in terms of ranking algorithms that are based on socializing links, as well as how search results can expose emergent properties of social consensus. An example of the latter arose as I was writing about the gorilla among wikis, and deciding how much that gorilla should weigh.  Let's check Google:

Weight of Gorilla (lbs.) Number of Google Hits 100 1,020 200 1,930 300 13,100 400 12,100 500 33,900 600 14,400 700 1,180 800 242,000 900 23,500 1000 915 1100 9 1200 353 1300 3 1400 8 1500 194 1600 214 1700 0 1800 57 1900 3 2000 1,380

Obviously, "800-pound gorilla" is the 800-pound gorilla of gorilla weights, even though adult males average about 400 pounds, are about 500 pounds at the extreme in the wild, and obese gorillas tip the scales at about 600 pounds in captivity.

Why 800? Maybe someone out there knows. What do you see in the other values? A 100-pound gorilla? Really? The values are higher around realistic gorilla weights, then drop off at 700 before spiking at 800. At 900 they are relatively high but then drop at again 1000. Why not 1000? Is it because people want to say an "X hundred pound gorilla" and not a "thousand pound gorilla" - so "ten hundred" doesn't work? Then, past 1000, there are some little spikes. Not 1100, but 1200. Not 1300 or 1400, but 1500 and 1600. I guess 1600 is two 800-pound gorillas. Then not a single 1700 pound gorilla to be found, but when you get to a ton, you're up there again.

This is a silly example, of course, but with a little thought, I'm sure you could construct some searches that show you social consensus points for other kinds of data.