Blogs are Op-Eds, Twitter is a Focus Group

That's the upshot of Mark McKinnon's latest:

Twitter is filling an important gap in the digital democracy -- a gap that most did not even know was there. If blogs are the inner monologues that occur after we have had a chance to sit down and think, then Twitter is the internal (albeit sometimes random) thoughts that most of us have all day long. Twitter allows us to tap into the collective brain; there is something very fascinating but strangely voyeuristic about this.

And (in contrast to my heading above):

Twitter is more than just a large, unorganized focus group; it is a link to real-time constituent consciousness.

An example:

For anybody who had his or her computer open to this page while watching the debate, it would have been hard not to notice the stark contrast between the stoic live audience and the very lively online audience. It was not as dramatic a shift as the first televised debates almost 50 years ago between Kennedy and Nixon, but more subtly suggested the game has changed.

Yes, sort of. I noticed that people in my Twitter stream all seemed to think that their candidate was creaming the other one -- even though they backed different candidates. Comments tended to focus on microlevel concerns such as candidates' facial expressions, verbal missteps, perceived slights, and imagined inner dialogues of the candidates. It makes sense that these spontaneous reactions came out of this spontaneous medium. Watching these Twitter streams allows you to see memes emerging, but also the prejudgments and entrenchments that people bring to the debates. They have to be triangulated with other, less spontaneous indicators to actually mean something for elections, I think.

You can't use Evernote for qualitative data analysis, even though it would be perfect

I mentioned a few days ago on my Twitter stream that qualitative data analysis tools are expensive and tended to lag other software, and that I preferred to build my own customized databases for QDA with MySQL and various front ends. More on that soon. But first, a few words about Evernote.

Evernote is described this way:

Evernote allows you to easily capture information in any environment using whatever device or platform you find most convenient, and makes this information accessible and searchable at any time, from anywhere.

Essentially, you install Evernote on all of your input devices, such as your laptop and iPhone, and capture the data you find most useful in the ways that you find most useful. So suppose that you see an interesting note on a whiteboard. You take a photo and it gets uploaded to Evernote. Text, audio, etc. all go to the same place and are accessible anywhere. Brilliant.

Whatever gets uploaded is "run ... through our recognition technology" and synchronized across all your input devices. Then you tag it and make notes. Tagging, of course, is a great way to code data. Now you have a vast, annotated, searchable database of heterogeneous data elements that can be accessed from anywhere and that is automatically synched (and therefore backed up). Perfect for qualitative data analysis, right?

Alas, no. Because any self-respecting institutional research board would balk at raw qualitative data being stored on a machine or server that is not owned and properly secured by the university. My IRB, for instance, specifies that data must be password-protected and stored on a hard drive that is encrypted at rest.

Hence I use a local, password-protected database running on an encrypted hard drive, and I set my screen saver to require a password for wakeup. I put audio, photos, etc. on the same hard drive. The drive gets backed up to a secure server. And anything I can't stick on the hard drive, such as physical collateral I pick up at the site, goes into a locked closet in my office.

Going to Iowa

Tomorrow I'll be flying to Iowa to visit my alma mater, Iowa State. Friday I'll deliver a rambling talk filled with personal anecdotes and accept an award.

If you're in the neighborhood, drop by!