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Unfortunately, running such experiments is easier said than done. In psychology experiments of the kind I discussed in the previous chapter, each “run” of the experiment involves at most a few individuals; thus conducting the entire experiment requires at most a few hundred subjects, typically undergraduate students who participate in exchange for money or course credit. The kind of experiment we had in mind, however, required us to observe how all these individual-level “nudges” added up to create differences at the collective level. In effect, we wanted to study the micro-macro problem in a lab. But to observe effects like these we would need to recruit hundreds of people for each run of the experiment, and we would need to conduct the experiment through many independent runs. Even for a single experiment, therefore, we would need thousands of subjects, and if we wanted to run multiple experiments under different conditions, we’d need tens of thousands.

In 1969, the sociologist Morris Zelditch described exactly this problem in a paper with the provocative title “Can You Really Study an Army in a Laboratory?” At the time, his conclusion was that you couldn’t—at least not literally. Therefore he advocated that sociologists should instead study how small groups worked, and rely on theory to generalize their findings to large groups. Macrosociology, in other words, like macroeconomics, couldn’t ever be an experimental discipline, simply because it would be impossible to run the relevant experiments. Coincidentally, however, the year 1969 also marked the genesis of the Internet, and in the years since, the world had changed in ways that would have been hard for Zelditch to imagine. With the social and economic activity of hundreds of millions of people migrating online, we wondered if it might be time to revisit Zelditch’s question. Perhaps, we thought, one could study an army in the laboratory—only this lab would be a virtual one.15

EXPERIMENTAL SOCIOLOGY

So that’s what we did. With the help of our resident computer programmer, a young Hungarian named Peter Hausel, and some friends at Bolt media, an early social networking site for teenagers, we set up a Web-based experiment designed to emulate a “market” for music. Bolt agreed to advertise our experiment, called Music Lab, on their site, and over the course of several weeks about fourteen thousand of its members clicked through on the banner ads and agreed to participate. Once they got to our site they were asked to listen to, rate, and if they chose to, download songs by unknown bands. Some of the participants saw only the names of the songs while others also saw how many times the songs had been downloaded by previous participants. People in the latter “social influence” category were further split into eight parallel “worlds” such that they could only see the prior downloads of people in their own world. Thus if a new arrival were to be allocated (randomly) to World #1, she might see the song “She Said” by the band Parker Theory in first place. But if she were allocated instead to World #4, Parker Theory might be in tenth place and “Lockdown” by 52 Metro might be first instead.16

We didn’t manipulate any of the rankings—all the worlds started out identically, with zero downloads. But because the different worlds were carefully kept separate, they could subsequently evolve independently of one another. This setup therefore enabled us to test the effects of social influence directly. If people know what they like regardless of what other people think, there ought not to be any difference between the social influence and independent conditions. In all cases, the same songs should win by roughly the same amount. But if people do not make decisions independently, and if cumulative advantage applies, the different worlds within the social influence condition should look very different from one another, and they should all look different from the independent condition.

What we found was that when people had information