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Giselle Weiss: Your early research is associated with the wildly popular idea of six degrees of separation, which far predates you. How did that idea spread?
Duncan Watts: I don't know. But the notion that we are all connected through a short chain of acquaintances has been around for a long time. It shows up in a 1929 short story called "Chains" by the Hungarian poet Frigyes Karinthy. And the urbanist Jane Jacobs speculated about it in her famous book, "The Death and Life of Great American Cities."
They didn't call it six degrees of separation, though.
No. That label comes from the title of a Broadway play of the 1990s by John Guare. The actual history is a little involved. But in any event, in 1967 psychologist Stanley Milgram set out to test the idea by having people in Boston deliver letters to people ("targets") in Omaha, Nebraska, through the intermediary of others known only on a first-name basis. He found that the average length of the letter chains that reached the targets was six. He called it the small world problem.
Where did your research come in?
In the 1990s, I was studying synchronization among crickets – who chirps with whom. Then one day on the phone, my dad asked me whether I'd ever heard of the idea that everyone is only six handshakes away from the president of the United States. It occurred to me that both problems involved networks, and that interested me.
What makes the idea so powerful?
We're attracted to the Enlightenment idea of ourselves as independent individuals who decide what we want to do and go out and do it. But the reality is that we're very much enmeshed in social relations. Everything we do and care about involves other people. These are network concepts.
Recently, you've been working on the structure of viral diffusion, for example, of tweets on Twitter. What's that about ?
We've been mapping the spread of information, particularly online. When you think about how information spreads, it's natural to liken it to the spread of a disease. In fact, people have been doing that for a long time in marketing. And it's been popularized in recent years by people like Malcolm Gladwell, author of "The Tipping Point," who very explicitly draws the analogy between the spread of behaviors or beliefs and diseases.
That sounds reasonable.
At a certain level, it is. But it's tempting to go a step further and apply the same mathematical models that have been developed to understand the spread of a disease to the spread of ideas or products.
What's wrong with that?
There are all sorts of models of how things spread, and they're often incompatible with each other. Moreover, we have very little data to test any of these models. For example, if you want to trace the spread of an idea, you have to be able to observe that person A has that idea, and then that person tells B, and then person B has the idea, and now person B tells person C. Mapping this out in a population of millions of people with hundreds of thousands and millions of things to observe is a tremendously difficult process.
So how do you approach it?
We've done a lot of work using Twitter data – news, media, images - where we can, to some approximation, observe everything. And we can also track exactly where everything is at a given point. People who study diffusion are generally looking for a critical threshold where ideas go from not spreading to spreading like wildfire.
And what have you found?
Initially, we found that nothing really spreads like that. In a study of millions of observations, 99 percent of everything that happened, every "adoption" of an idea, was within one degree of the source. Which is almost the opposite of spreading. In other words, I tweet something and you re-tweet it. Your followers see your re-tweet, but they don't do anything. It's the re-tweet that we pay attention to. When we described this result to our colleagues, however, they often didn't like it.
People are convinced that certain things "go viral," and that's what interests them. So they would say, "We know some things spread. Look at ‘Gangna