measuring the pace of spread
May 3rd, 2009 • posts i've written
Faris has written a great observation piece on the pace of cultural latency.
Diminished cultural latency means that the propagation of information is so fast that the spread itself becomes the defining aspect of the system: the rate-of-spread becomes as important as the information itself.
That rate of spread has consumed me for the better part of the last two years. I’m a measurement addict. I crave knowing the deep, dark secrets of the data universe. And what’s more, I crave every bit of competition, and knowing where you and your opponent stand (not too even mention how well I alone am doing). We often work with clients that release content into the web, and I have been tense with not knowing how well that information has spread.
So many factors go into releasing that content: what communities we choose to tap, how well they’re connected, how much social currency is baked into the content for that community, the novelty factor, which platforms we choose, what account we release from, how we title it, what tags we use, what time of day, what day of the week, what other information is spreading within the network, etc. etc. Ultimately though, for this mountain of criteria, our feedback mechanism is lousy. It’s like swimming in the Olympics and being given a time, without rank, without seeing the other swimmers, without the start gun, and without any knowledge of how to swim.
I’ve been obsessing about this, obviously. What I’ve been looking for is a way of understanding the ‘speed of light’ for YouTube, specifically. (admittedly, not the greatest metaphor) What’s the asymptotic curve of how quickly content is spreading in that platform alone, say for the last 2 years? What are we approaching in terms of time between views, or looking outside of that platform alone, time between sharing? Perhaps every bad decision we make in creating, courting, and releasing that information can be likened to friction, and we can begin to measure and better understand that effect in what we do.
If I could choose at random, 150 new videos per day, to track their pace from upload to six months in, what could we learn about the speed of information spread? This question is certainly more vexing when you open it up to events in the world (how quickly swine flu information spread online for example), as well. But YouTube provides a perfect petri dish for discovery (and YouTube study and findings could prove somewhat lucrative as well).
So, is anyone up for the challenge? And can I help?
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