Via Slashdot, investigative journalist John Mecklin lays out a way that the Internet revolution is actually helping journalism (crazy, I know):

Now, in the post-Google Age, Allison sees the possibility that computer algorithms can sort through the huge amounts of databased information available on the Internet, providing public interest reporters with sets of potential story leads they otherwise might never have found. The programs could only enhance, not replace, the reporter, who would still have to cultivate the human sources and provide the context and verification needed for quality journalism. But the data-mining programs could make the reporters more efficient — and, perhaps, a less appealing target for media company bean counters looking for someone to lay off.

IMHO, the part about investigative reporters not getting laid off seems increasingly far-fetched.  There are problems in the news business that a few new reporting techniques won't solve.  But still, increasing the efficiency with which the public can gain from its own data is something worth cheering.  As I've tried to stress throughout my posts, the ability to search through massive databases of material like this is still in its infancy.  Our ability to collect information has outstripped our ability to make sense of it, and we're still growing into all the things we can do with this data.

(I meant to do this last week, but I was visiting family in Asia, and damn it, Firefox ate my post again. Sorry about that. - DD)

We left off talking about how important it is to know your client:

When you are doing research for someone, they are entrusting you to discover what they need to accomplish their goals. It's an incredible responsibility, and not one that you should take lightly.  In order to understand their needs, you have to understand them.  You have to understand their organizational mission, their history, their resources in addition to the parameters of your specific project.  Unless you know your client, all the time and resources you put into it will be for naught.

The goal was to leave off and use the absence to see what we could find.  We'll see what we found out under the flip.

When we started this site, we never meant to let our partisan identification get have anything to do with what we wrote about. After all, when writing about data, voter files, polling, journalism, microtargeting, Linux and other such things, you'd think that there would be plenty of material to write about.  And, well, there is, but to my eyes, the perpetrators of stupidity in polling are mostly on the otherside.

Today's lesson comes from that bastion of truth-seeking and truth-speaking integrity, the Editorial Pages of the Wall. St. Journal.  Known parrhesiast Stephen Moore decides to show us how not to read a poll.

There's more.

This summary of all the reasons that the GOP is in a deep hole and won't be climbing out anytime soon--from Tom Edsall at the Huffington Post--is sure to fill you with holiday cheer.

OK, maybe your version of holiday cheer doesn't mean "revelling in the destruction of your enemies".  Don't judge my family! I had an almost normal childhood!

Portfolio, oddly enough, has a good interview with David Plouffe, Obama's campaign manager; it's a good backgrounder and has some interesting thoughts.  Worth checking out.

Far be it from me to ever, ever think that I could be better at reading data than Steven Levitt. I've been a big fan of his since back when he was putting out studies on crime rates at The Harvard Society of Fellows, and I think that there are few people who are as capable of looking at data without predisposition as he is, and, let's be honest, Freakonomics was the book in 2005. That being said, there are times when I read his NYT blog and wonder what the hell is going there. Today's guest post from Eric Oliver was one of those times.

There's more.

Those of you following along at home may notice that this post has introduced some new categories to the list, and that's because there's no really easy way to categorise this.  Basically, not too long ago, two of the entities listed on this site as Inspirations, RealClearPolitics and FiveThirtyEight, got into a major slapfight over different methodologies, transparency and whether or not one of them was committing major fraud in an effort to drive the media.

Here's the context: Nate Silver wanted to know why RCP wasn't including the Research 2000 polls commissioned by Daily Kos, but would include the polls by the Associated Press.  Silver argued that it was because the R2K polls were showing massively favorable Democratic results, while the AP was finding better results for the Republicans.  Since the editorial position of RCP is Republican, he argued that they had a vested interest in promoting better numbers for McCain, and that he had caught them doing it.

As much as I like Nate, though, I think that he's wrong, but he has managed to touch on one of the most fascinating things about the internet: the way that professionals and pitted against knowledgable impassioned people, and how this results in different models of information dissemination.

There's more...

I think everyone in politics wants, just once, to be Josh Lyman in that scene from the first West Wing episode where two college girls fangirl on him at a restaurant.  Luckily, the Internet is here to make this a reality for a lucky few.  I can sort of understand--if not participate in--the impulse behind Viva Chuck Todd!. 

But...seriously...David Gergen?!?@?!?!?!@!11111!

I can't deal with this, not today.

We're back with another liveblog!

We're back, and tonight's post is about CNN's dial groups.  Dial groups are a form of focus group in which people are sampled by strata and given a handset. This handset has an analog dial that allows people to indicate their responses to stimuli, favorable to unfavorable, usually graduated 1 to 100.  The output from these handsets are then aggregated by strata and averaged to produce a function of time. Here's an example:

CNN has put together a group of 99 people from the state of Ohio. This group is 33 Republicans, 33 Democrats and 33 Undecided/Independent voters.  All the output from the each group's handsets will be added together and divided by 33, and then that number will be graphed as the y variable, with time as the x variable.  Each stratum will be given its own function.  That way, you can see how people are reacting in real time to the speeches or events.

There's more...