Making mistakes as a research method

A blog called SloshSpot ran an article entitled "The 10 Oldest Bars in the United States."
How did the author do his research? No idea. Whatever steps he took, he was wildly inaccurate, as many commenters on Digg.com and SloshSpot were quick to point out.
People were so quick to point out older bars that he had missed, that a thought struck me. How quickly would he have been able to solicit answers if he had simply run an article asking for the oldest bars in the United States?
By baldly stating that his list was correct, the author spurred a lot of people into action. Annoyed, indignant, completist, helpful, proud, angry, or just plain old knowitall, it doesn't matter - the rebuttals came fast.
Could it be that the best way to get answers from a large segment of people is to deliberately proclaim the wrong answers in public first?
The original list, and the updated, user-supplied corrections, after the jump.
Action heroes
A Digg user submitted a story showing a remarkable similarity between Jefferson and another great action hero, Steven Segal: http://digg.com/odd_stuff/Coincidence_of_Currency_Shows_Similarity_in_Two_Great_Men
Turns out this holds true for quite a few action heroes...

Blanche Lincoln

Arkansas Senator Blanche Lincoln might be the best running mate for Obama in this election. She's young (48), a great speaker, attractive, strong, and has the right mix of conservative and liberal values to sway Clinton voters and even some Republicans.
Presidential politics are partially about issues, and Lincoln has an excellent resume there, but they are also much more about impressions than some people would like to believe.
She's got a wonderful voice that can enchant an audience, and a name like Lincoln is hardly a liability.
I first paid attention to Senator Lincoln in '04, and I still believe that she is a rising star. I expect to see this woman in the White House one day - might as well start as Obama's VP.
Corporate diversity
Lazy designers and timid communication departments love stock photography, and most of all corporations love safely diverse stock photography.
Bizarrely enthusiastic Smiling LadiesTM aside, I'd like to see an audit done someday of how various ethnicities are portrayed in all these images. From the tableaux we choose, an outside observer might conclude that every group of white friends has one or two black friends, and occasionally the lone female Asian companion. Hispanics, South Asians, and Middle Easterners do not exist at all, of course, unless it's a "special" or "ethnic" communication (generally not in English).
Most tellingly, watch for the placement of people in these Diversity Photos - you're not going to see whitey sitting in the back seat by herself:

What's a Digg worth?
Here's a comparison of two events from Digg.com and how they translated into actual website visitors.
The first is a front page story on Digg.com - in this case, a survey I put up in August 2007. The story, "What do Digg users think of the world?." received 5045 diggs.

The story linked to a ten question survey, which was completed by 45,000 people. I don't have stats on the total number of visitors that didn't complete the survey, unfortunately. The survey did not require users to answer every question, so the completion rate of 100% includes anyone who gave even one answer out of ten.
In this case, a front page story on Digg.com in mid-2007 equated to about 9 completed surveys per digg - and an unknown number of visits without user action.

The second is a comment on another person's story on Digg. This story was about a new concept car from Toyota, and the story itself had 962 diggs. My comment, a response to another person's comment (which itself had 124 diggs), had a total of 3 diggs.

In that day, there were 104 unique visitors to the linked story (Tokyo Motor Show).


There are three ways to interpret this:
A comment on a front page Digg story translates to either:
One visit for every 9 diggs (based on the popularity of the story)
One visit for every one comment digg (based on the parent comment)
or
35 visits for every comment digg (based on the popularity of the comment itself).