The small sample size of Stanley Milgram’s small world experiment means that the theory of ‘six degrees of separation’ and the conclusion drawn from it–primarily, the Influential’s theory popularised by Malcolm Gladwell in The Tipping Point–could be deeply flawed. That was the starting point for Duncan Watts‘ research that led him to say “the Tipping Point is toast”.
So to research how ideas and trends spread virally, Watts (who is author of Everything is Obvious, principal research scientist at Yahoo! Research (he directs their Human Social Dynamics group), and founding director of Columbia University’s Collective Dynamics Group) ran large-scale reproductions of the small world experiment and hundreds of computer simulations that brought forward two conclusions: the six degrees of separation theory is correct, but there is no evidence for super-connected ‘trend gatekeepers’ (such as Gladwell’s ‘Connectors’):
But Watts, for one, didn’t think the gatekeeper model was true. It certainly didn’t match what he’d found studying networks. So he decided to test it in the real world by remounting the Milgram experiment on a massive scale. In 2001, Watts used a Web site to recruit about 61,000 people, then asked them to ferry messages to 18 targets worldwide. Sure enough, he found that Milgram was right: The average length of the chain was roughly six links. But when he examined these pathways, he found that “hubs”–highly connected people–weren’t crucial. Sure, they existed. But only 5% of the email messages passed through one of these superconnectors. The rest of the messages moved through society in much more democratic paths, zipping from one weakly connected individual to another, until they arrived at the target. […]
[His computer simulation] results were deeply counterintuitive. The experiment did produce several hundred societywide infections. But in the large majority of cases, the cascade began with an average Joe (although in cases where an Influential touched off the trend, it spread much further). To stack the deck in favor of Influentials, Watts changed the simulation, making them 10 times more connected. Now they could infect 40 times more people than the average citizen (and again, when they kicked off a cascade, it was substantially larger). But the rank-and-file citizen was still far more likely to start a contagion.
I can’t help but find it somewhat ironic that, written almost four years ago, this argument hasn’t really gained much traction and Gladwell’s ideas are still discussed ad nauseam.