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By Root 1010 0

such an idea would be laughable. Yet when we see something special happen in the social world, we are instantly drawn to the idea that whoever started it must have been special also. And of course, whenever a large cascade did take place in our simulations, it was necessarily the case that someone had to have started it. However unexceptional that person might have seemed in advance, in retrospect they would seem to fit exactly the description of the law of the few: the “tiny percentage of people who do the majority of the work.” What we knew from our simulations, however, was that there really was nothing special about these individuals—because we had created them that way. The majority of the work was being done not by a tiny percentage of people who acted as the triggers, but rather by the much larger critical mass of easily influenced people. What we concluded, therefore, is that the kind of influential person whose energy and connections can turn your book into a bestseller or your product into a hit is most likely an accident of timing and circumstances. An “accidental influential” as it were.22

“ORDINARY INFLUENCERS” ON TWITTER

As many people immediately pointed out, this conclusion was based entirely on computer simulations. And as I’ve already mentioned, these simulations were highly simplified versions of reality, and made a large number of assumptions, any of which could have been wrong. Computer simulations are useful tools that can generate great insight. But in the end they are more like thought experiments than real experiments, and as such are better suited to provoking new questions than to answering them. So if we really want to know whether particular individuals are capable of stimulating the diffusion of ideas, information, and influence—and if these influencers exist, which attributes distinguish them from ordinary people—then we need to run experiments in the real world. But studying the relationship between individual influence and large-scale impact in the real world is easier said than done.

The main problem is that you need an enormous amount of data, and most of it is very hard to collect. Just demonstrating that one person has influenced another is difficult enough. And if you wanted to make the connection to how they influence larger populations, you need to gather similar information for whole chains of influence, in which one person influences another who in turn influences another, and so on. Pretty soon, you’re talking about thousands or even millions of relationships, just to track how a single piece of information was spread. And ideally you would want to study many such cases. It’s an over-whelming amount of data to test what seems to be a relatively straightforward claim—that some people matter more than others—but there’s no getting around it. It also helps explain why diffusion research, as it is known, has remained such a myth-laden business for so long: when it’s impossible to prove anything, everyone is free to propose whatever plausible story they like. There’s no way to decide who is right.

As with experiments like Music Lab, however, the Internet is starting to change this picture in important ways. A handful of recent studies have begun to explore diffusion in social networks on a scale that would have been unimaginable just a decade ago. Blog postings diffuse among networks of bloggers. Fan pages diffuse among networks of friends on Facebook. Special capabilities called “gestures” diffuse among players on the online game Second Life. And premium voice services have been shown to diffuse among networks of IM buddies.23 Inspired by these studies, my Yahoo! colleagues Jake Hofman and Winter Mason and I, along with Eytan Bakshy, a talented graduate student at the University of Michigan, decided to look for the diffusion of information in the largest communication network we could get our hands on: Twitter. In the process, we would look for influencers.24

In many respects, Twitter is ideally suited to this objective. Unlike Facebook, say, where people connect to one another