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showed the importance of social influence in determining success, involved nearly thirty thousand participants. One could have dreamed up this experiment fifty years ago—back when social psychologists were first pioneering experimental studies of influence and group decision making—but it would have been impossible to conduct it until recently for the simple reason that you can’t fit that many people in a physical lab. Likewise, the “influencers” study on Twitter that I discussed in Chapter 4 was designed to answer a question—about whether or not special individuals cause information to spread—that has been around for decades. Answering it, however, required us to track the diffusion of more than 70 million URLs over the entire Twitter network for a two-month period. Prior to social networking services like Twitter and Facebook, which, remember, are just a few years old, that level of scale and resolution would have been impossible.14

Other experiments that I have described, like the Small World experiment from Chapter 4, were certainly possible in the pre-Internet era, but not on the scale at which they can now be conducted. Milgram’s original experiment, for example, used physical letters and relied on just three hundred individuals attempting to reach a single person in Boston. The e-mail–based experiment that my colleagues and I conducted back in 2002 involved more than sixty thousand people directing messages to one of eighteen targets, who in turn were located in thirteen countries. In the course of being delivered, the message chains passed through more than 160 different countries; thus for all its limitations, the experiment was at least a crude test of the small-world hypothesis on a truly global scale. Likewise, David Reiley and Randall Lewis’s field experiment on ad effectiveness, described in Chapter 8, was similar in design to experiments that had been conducted in the past, but with 1.6 million participants, it was many times larger. The sheer scale of the exercise is impressive simply on the grounds that it can be done at all, but it’s also important scientifically—because it’s possible that the effects, while real, can be small, in which case one needs very large numbers to tease them out of the noise.15

BIRDS OF A FEATHER

Another kind of study that would have been impossible to conduct until recently concerns one of the most widely observed patterns in social life, known in sociology as the homophily principle—the idea that “birds of a feather flock together.” For several decades now, wherever sociologists have looked they have found that friends, spouses, coworkers, and social acquaintances are more similar than strangers with respect to a whole range of attributes—like race, age, gender, income, education—and also attitudes. But where does all this similarity come from? At first, the answer seems obvious: People are likely to form ties with others who are similar because, rightly or wrongly, that’s whom they’d prefer to spend their time with. But what this commonsense explanation overlooks is that people can only choose their friends from among the people they actually meet, which is determined to a large extent by the people they work with, or who belong to the same organizations, or to whom they are introduced by mutual acquaintances. And as sociologists have also shown, many of these social environments tend to be highly homogeneous in terms of race, gender, age, and education. As a result, it is entirely possible that the similarity we see around us has less to do with our own psychological preferences than the restricted opportunities that the world presents to us.16

Resolving problems like this one is important because it has implications for how we go about dealing with controversial issues like racial segregation and affirmative action. Settling the matter with data, however, is extremely difficult because disentangling the various cause-and-effect relationships requires one to keep track of individuals, networks, and groups over extended intervals of time.17 And historically, that sort of