Social Scenes: The Invisible Calculus Of Culture
Today, in New York, I heard Clay Shirky talk two times — midday at the Betaworks monthly Brown Bag Lunch, and this evening at the New York Tech Meetup — on the same topic. He is extrapolating in very interesting ways from the research of social scientists Nicholas Christakis and James Fowler on the social dimension buried in the data of the Framingham Heart Study.
In a nutshell, it turns out that the activities of the ‘third neighborhood’ influence you in ways you may be completely unaware of. These are people that you do not know, but are (dis)connected to you by two removes: the friends of your friends’ friends. Christakis and Fowler found that obesity, smoking, and many other medical factors strongly correlated with the prevalence of corresponding activities in these large social scenes:
- Clive Thompson, Are Your Friends Making You Fat?
Christakis knew about the Framingham Heart Study and arranged a visit to the town to learn more. The study seemed promising: he knew it had been underway for more than 50 years and had followed more than 15,000 people, spanning three generations, so in theory, at least, it could offer a crucial moving picture. But how to track social connections? During his visit, Christakis asked one of the coordinators of the study how she and her colleagues were able to stay in contact with so many people for so long. What happened if a family moved away? The woman reached under her desk and pulled out a green sheet. It was a form that staff members used to collect information from every participant each time they came in to be examined — and it asked them to list all their family and at least one of their friends. “They asked you, ‘Who is your spouse, who are your children, who are your parents, who are your siblings, where do they live, who is your doctor, where do you work, where do you live, who is a close friend who would know where to find you in four years if we can’t find you?” Christakis said. “And they were writing all this stuff down.” He felt a jolt of excitement: he and Fowler could use these thousands of green forms to manually reconstruct the social ties of Framingham — who knew whom, going back decades.
Over the next few years, Christakis and Fowler managed a team that painstakingly sifted through the records. When they were done, they had a map of how 5,124 subjects were connected, tracing a web of 53,228 ties between friends and family and work colleagues. Next they analyzed the data, beginning with tracking patterns of how and when Framingham residents became obese. Soon they had created an animated diagram of the entire social network, with each resident represented on their computer screens as a dot that grew bigger or smaller as he or she gained or lost weight over 32 years, from 1971 to 2003. When they ran the animation, they could see that obesity broke out in clusters. People weren’t just getting fatter randomly. Groups of people would become obese together, while other groupings would remain slender or even lose weight.
And the social effect appeared to be quite powerful. When a Framingham resident became obese, his or her friends were 57 percent more likely to become obese, too. Even more astonishing to Christakis and Fowler was the fact that the effect didn’t stop there. In fact, it appeared to skip links. A Framingham resident was roughly 20 percent more likely to become obese if the friend of a friend became obese — even if the connecting friend didn’t put on a single pound. Indeed, a person’s risk of obesity went up about 10 percent even if a friend of a friend of a friend gained weight.
“People are connected, and so their health is connected,” Christakis and Fowler concluded when they summarized their findings in a July 2007 article in The New England Journal of Medicine, the first time the prestigious journal published a study of how social networks affect health. Or as Christakis and Fowler put it in “Connected,” their coming book on their findings: “You may not know him personally, but your friend’s husband’s co-worker can make you fat. And your sister’s friend’s boyfriend can make you thin.
Obesity was only the beginning. Over the next year, the sociologist and the political scientist continued to analyze the Framingham data, finding more and more examples of contagious behavior. Smoking, they discovered, also appeared to spread socially — in fact, a friend taking up smoking increased your chance of lighting up by 36 percent, and if you had a three-degrees-removed friend who started smoking, you were 11 percent more likely to do the same. Drinking spread socially, as did happiness and even loneliness. And in each case one’s individual influence stretched out three degrees before it faded out. They termed this the “three degrees of influence” rule about human behavior: We are tied not just to those around us, but to others in a web that stretches farther than we know.
This research brings to mind the obsrvation of Blaise Pascal, “The heart has its reasons that the mind knows not.” It appears that negative behaviors like overeating and smoking are in some hidden way transmitted through our social networks, even when we are not in contact with those others who are influencing us. Likewise, it turns out that happiness is spread in a similarly diffuse and oblique fashion.
Getting back to Clay: he wonders what this means for the way that modern social tools work, like Twitter, for example.
In social tools, we are each the center of our own universe, and we are connected to our friends (who are each the center of their own universes, too). We are aware that our friends have friends we don’t know (or are aware of in the most insubstantial of ways). And these friends of friends likewise have friends, which are unknown to us as well.
But despite their anonymity and distance from us, they are influencing us, as Christakis and Fowler showed. But out tools, like Twitter, don’t allow us to deal with this mass of people — which is likely to be on the order of a million people, plus or minus — in any way at all. It is not addressible, or searchable, or filterable. I can’t find out what TV my social scene is watching, or what music they like, or how they voted in the last election.
Shirky points out that it is easy to find out what my friends are doing, or what the world as a whole is doing, but what the world is doing is fairly ‘bland’ as he puts it. The world’s combined interests lead to the dropping out of all the odd and eclectic, and you are left with Lady Gaga and Obama. BIg surprise.
But my social scene — the group that actually influences my thinking, moods, and buying behavior — in completely untapped and untappable by out tools today.
However, its clear that it could be tapped: just as in the Framingham Heart Study. It’s possible (and not even very technically challening) to create the swirling, dynamic, and ever-changing opinions and activities of your one million closest ‘friends’, only a few hundred that you know well and perhaps a few thousand that you ‘know of’. We are all surrounded by ‘dark matter’, the next ring in the social cosmology out past those you know and the friends of those you know: a million people exerting an invisible influence on those that influence those that influence you. If that group is down on smoking, you will be getting social cues to not smoke. If they are crazy about Korean food, you will be served kim chi at dinner parties. If they are into country and western music, you will find yourself shopping for cowboy boots with your cousin.
Shirky clearly states that he doesn’t know where this will lead, even if he is right. But I think that it is obvious that we would like to explicit see and measure the influences in our unverse (each in their own overlapping universes), so on a personal level this may be a tremendous adjunct to the filtering, amplifying, and serendipity that we all want social tools to help us with. And perhaps just as much as a possible driver of technical experimentation in this sector, companies would like to know how influence is channeled and how it impacts individuals. The underbelly of this is exactly that: that marketers would like to tap into this social juju, and influence us through social ties that we can’t even touch directly.
But it is always the brightest light that casts the darkest shadow.
It comes as no surprise that there is value — and power — in identifying the wellspring of our desires and the foundation of our apsirations. Social scenes may turn out to be the crux of this transitive and reflexive influence that we exchange in ten thousand ways, every day. If it turns out that our place in the world — our position in an invisble sphere of one million almost friends of ours — defines strongly who we are, what we love, and who we hate, would we be surprised? Not me.
This may be just the face of tribalism, proven through scientific observation. I am choosing to use the term ‘social scene’ though, because tribalism has so many connotations and associations that could take us off the track. Also, it was Brian Eno that coined the term ‘scenius’ to represent the positive side of a social scene:
via Kevin Kelly, quoting Brian Eno
Scenius stands for the intelligence and the intuition of a whole cultural scene. It is the communal form of the concept of the genius.
We are a result of the accumulated sum of influences that are being tallied behind our backs, and behind the backs of all those that we know. Apparently, we are impacted by a hidden calculus in which we are the integral of the specturm of influences on all those we hold dear.
The Bantu people have a saying “Through people we become human,” and ever aspect of our identity and psychology is shaped by the cultural milieu in which we are part. I have said for years, “I am made greater by the sum of my connections, and so are my connections,’ alluding in a recursive way to these hidden network dynamics. And of course we want better tools to bring these indistinct and indirect forces into high relief. Clay is right about that.
