What is the idea then? Well, it's actually really simple. Think about the Twitter network, the kind of people who connect there, and the way things spread. What is the difference between Twitter and mobile texting for example? First, everything is by default multicast. It's not reciprocal - you don't need to know how many hundreds or thousands read what you write. And you don't care how many others read the persons you read. You are restricted in length. And, the whole thing is open enough that you can follow all the tweets going on in the system.
The characteristics I've described means that Twitter is more or less the ideal memetic engine. What I mean by this is that it's a wonderful way to spread your ideas, if you can express them in a concise and readable way. This means that certain memes doesn't work well in this setting, but most do. And you can convince more people to join, because if your tweets are interesting enough, someone will notice them in the all-tweet. Also, you can see who the people you are interested in follows, which means that you can spread your network selectively, but really quickly.
These are not really part of the theory. They are just the axioms. So what's the theory then? Well, what are Twitter doing with all this data? If I would have been them, I would have used it to do research on memetic spread and viral marketing. I would use it to try out ideas based on how good uptake they have. Finding this information is not really hard when you have control over all the messages happening. In fact, you could actually do it even outside of Twitter, by using the published tools correctly.
What got me thinking along these lines? Well, the whole TechCrunch debacle was the thing that triggered the idea. How would it work in practice? Well, first, the Twitter gang couldn't necessarily know what kind of people would take up Twitter the most, so the cultural fit of Twitter is actually mostly self organizing. The people and groups taking part of twitter select themself for this experiment. Now, of course there are lots of overlapping groups, and that gives even more interesting possibilities for the sociodynamics of meme transfer between non-overlapping social circles.
Take the Ruby people, who have a quite significant presence on Twitter. They are one of the test groups in my theory, and the TechCrunch article was a very directed way of inserting a meme and see how fast and to how many it propagated. It was very easy to insert this into the blog-sphere, since Twitter could have had any amount of people "leak" the information in the TechCrunch article. Once it was out, they just needed to set up some suitable filters and follow the spread. They also inserted a couonter meme, through one of their employees, to see if it work out as an "antidote" to the first meme, or which one of them was stronger. All in all, I think they got enough material for several research articles out of this stunt.
OK, so really, you don't need to grasp for conspiracy theories to explain the TC debacle. It's not necessary, so Occam's razor demands that we choose the simplest available conclusion that explains all the facts. This theory does not fall into this category. But it's still an entertaining notion.
And I predict that sooner or later, someone will use Twitter, or another network like it, to do this kind of research. It's a question of time. This kind of information is way to valuable for marketing purposes and also for the understanding of the human mind, that it will happen. The question is: will you know about it, when you're participating in their research?
Let's not forget the lovely recursive interpretation that this blog post is a way of doing the same kind of research I've just described.