Bloggasm

Yesterday PBS published an article of mine about Web 2.0 tools that people are using to aggregate data on the election.

One that I didn’t get a chance to mention is one I’m working on for my day job at New Media Strategies: Freshly Squeezed Election Tweets

Here’s a rundown of some of its features:

What is it?

It’s an abstract visualization of the aggregate conversation on the popular social media platform, Twitter, showing frequency and context of election-related words.

How does it work?

We take a sample from Twitter every 30 seconds and analyze them in 50-result batches for associations and term matches. They accumulate for 5 minutes and then we flush sample aggregates to the database. As new terms trend, they begin to populate on the X-axis.

Wait, say that again?

The site will pull a continuous stream of tweets mentioning Obama and McCain, representing the most-used terms as a series of bubbles. The bigger the “bubble” the more frequently the term is being used.

So what am I looking for?

Each bubble is colored red and blue: the more red, the more the term correlates with McCain, the more blue, the more Obama. Keyword bubbles are themselves connected by half-circles (solid colors only), showing relationships between them. The stronger the connection, the thicker the line. And a bit later today, we’ll add a feature so you can sort by time periods.

A tee-shirt that lights up when you get close to a wireless hot-spot.

So as I mentioned previously I’m starting my new job as an online analyst at New Media Strategies on Sept. 10. The downside of this is the fact that I’m missing out on all the kick ass stuff they’re doing at the two party conventions. As I write this, a few of my coworkers are at the Pepsi Center with credentialed blogger passes.

I’m also having to miss out on the work they’re doing with C-SPAN. They’ve created an entire convention hub for both Democrats and Republicans. Over the next two weeks my future coworkers are providing around-the-clock coverage of the blogosphere, particularly focusing in on those blogs that are covering the conventions. The Hub also includes Twitter feeds and NMS employees are on the ground at the conventions themselves in order to facilitate the coverage.

William Beutler has a good summary of what they’re doing and the hub has also been picked up by TechCrunch and several other major sites.

But I still have to wait two more weeks before I can join in on the action. By then, the conventions will be long over with.

We’re not always nice when talking about Chris Matthews, but in the Youtube video below you’ll find him at the top of his game:

In the lead-up to the Indiana and North Carolina primaries, most television news pundits were relying on polls from professional pollsters — like Zogby — to predict the outcome. But a pseudonymous blogger known as Poblano was using a different methodology — demographics.

Guess whose predictions were more accurate?

“Critics scoffed. Most of the public polls pointed to a close race in North Carolina,” writes the National Journal. “Looking back at Poblano’s efforts in Pennsylvania, pollster Dick Bennett decried the models as ’stepwise regression run amok.’ Slate’s Mickey Kaus predicted failure for ‘a sophisticated model that ignores… what’s been happening in the campaign. Like Rev. [Jeremiah] Wright.’”

But in the end, they were wrong and Poblano was right.

What’s perhaps scary is that he was able to make these predictions based on demographic sub-groups. Are they really that predictable? Is this evidence that no matter what happens in a campaign, these subgroups will always vote the same?

The National Journal article has a nifty chart that gives a clear picture of how accurate the blogger’s results were compared to all the professional pollsters.

“Crowd sourcing” is a buzz phrase often employed in conversations about new media. In theory, online media outlets will be able to utilize the wisdom of the crowd (i.e. their readers) to find out first-hand information about certain subjects. One of the most famous examples of this is the blog Talking Points Memo utilizing its readership to uncover the U.S. Attorney firings scandal.

Lately, though, I’ve seen a number of stories highlighting another way of using online crowd wisdom: Crime solving.

The latest example of this appears in a New York Times article. Two thieves pull up to a car dealership and take a relatively rare car on a “test drive.” They never return with the car, and not long afterwards the dealer posts a note on an online forum giving the details of the theft. After multiple sightings of the car, the implementation of both Google Maps and Facebook, and several camera phone pictures of the thief, the guy was nabbed and the dealer got his car back.

The NY Times article has dubbed this tactic “open source crime solving.” Now if only someone could create a website specifically for this specific kind of crowd sourcing.

…So you can post youtube videos of a song you created using only sounds that come from Windows XP and 98 computers. You have to watch the Youtube video embedded below to know what I mean: