Duncan Watts, a Yahoo! researcher who studies networks, has some interesting things to say:
“If society is ready to embrace a trend, almost anyone can start one–and if it isn’t, then almost no one can,” Watts concludes. To succeed with a new product, it’s less a matter of finding the perfect hipster to infect and more a matter of gauging the public’s mood. Sure, there’ll always be a first mover in a trend. But since she generally stumbles into that role by chance, she is, in Watts’s terminology, an “accidental Influential.”
Epidemics and many other contagion phenomena have a power-law distribution (large frequency of small number infected, small frequency of large number infected). When my colleagues and I studied the distribution of rat bar-press durations, we found a power-law-like function where the “size” wasn’t number but duration. Most bar-presses were quite short; a few were quite long. We also found that expectation of reward had a big effect on the slope of the power-law function. I think Watts is saying that more attention should be paid to what determines the slopes of these power-law functions.
A recent article by Watts. Thanks to Hal Pashler.
When talking about trends, it seems like it’s not the first person who is influential, so much as the first group. That is, first a group within a culture adopts a certain practice, then the larger culture adopts it or not. The first person within the group is not so important, maybe.
I wonder if the same can be said of contagion.
Thanks so much for the link to this article. You didn’t even mention, the root of the study is new mass experiments that don’t confirm the folklore science of influence that spews from the mouths of experts without data or confirmation. So much of our science is data-free posturing. Are we on the cusp of a new scientific revolution? One that finally jettisons the pretenses of academic theory and demands only data?