Posted by The Situationist Staff on March 3, 2008
Nicholas Christakis describes his research with James Fowler on social networks, and how he came to that research, on Edge. We have posted some excerpts from the fascinating video and transcript below.
There is a well-known example in evolutionary biology about whether the eye was designed, or is “just so” because it evolved and arose for a reason. How could this incredibly complicated thing come into being? It seems to serve an incredibly complicated purpose, and the eye is often used in debates about evolution precisely because it is so complex and seems to serve such a specialized and critical function.
For me, social networks are like the eye. They are incredibly complex and beautiful, and looking at them begs the question of why they exist, and why they come to pass. Do we need a kind of just-so story to explain them? Do they just happen to be there, for no particular reason? Or do they serve some purpose — some ontological and also pragmatic purpose?
Along with my collaborator James Fowler, I have been wrestling with the questions of where social networks come from, what purpose they serve, what rules they follow, and what they mean for our lives. The amazing thing about social networks, unlike other networks that are almost as interesting — networks of neurons or genes or stars or computers or all kinds of other things one can imagine — is that the nodes of a social network — the entities, the components — are themselves sentient, acting individuals who can respond to the network and actually form it themselves.
In social networks, there is an interdigitation between the higher order structure and the lower order structure, which is remarkable, and which has been animating our research for the last five or ten years. I started by studying very simple dyadic networks. A pair of individuals is the simplest type of network one can imagine. And I became curious about networks and network effects in my capacity as a doctor who takes care of people who are terminally ill.
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For example, one day I met with a pretty typical scenario: a woman who was dying and her daughter who was caring for her. The mother had been sick for quite a while and she had dementia. The daughter was exhausted from years of caring for her, and in the course of caring, she became so exhausted that her husband also became sick from his wife’s preoccupation with her mother. One day I got a call from the husband’s best friend, with his permission, to ask me about him. So here we have the following cascade: parent to daughter, daughter to husband, and husband to friend. That is four people — a cascade of effects through the network. And I became sort of obsessed with the notion that these little dyads of people could agglomerate to form larger structures.
Nowadays, most people have these very distinct visual images of networks because in the last ten years they have become almost a part of pop culture. But social networks were studied in this kind of way beginning in the 1950s . . . . But all these were still very small-scale networks; networks of three people or 30 people — that kind of ballpark. But we are of course connected to each other through vastly larger, more complex, more beautiful networks of people. Networks of thousands of individuals, in fact. These networks are in a way living, breathing entities that reproduce, and that have a kind of memory. Things flow through them and they have a purpose and can achieve different things from what their constituent individuals can. And they are very difficult to understand.
This is how I began to think about social networks about seven years ago. At the time when I was thinking about this, I moved from the University of Chicago to Harvard, and was introduced to my colleague James Fowler, another social scientist, who was also beginning to think about different kinds of network problems from the perspective of political science. He was interested in problems of collective action — how groups of people are organized, how the action of one individual can influence the actions of other individuals. He was also interested in basic problems like altruism. Why would I be altruistic toward somebody else? What purpose does altruism serve? In fact, I think that altruism is a key predicate to the formation of social networks because it serves to stabilize social ties. If I were constantly violent towards other people, or never reciprocated anything good, the network would disintegrate, all the ties would be cut. Some level of altruism is required for networks to emerge.
So we can begin to think about combining a broad variety of ideas. Some stretch back to Plato, and thinking about well-ordered societies, the origins of good and evil, how people form collectives, how a state might be organized. In fact, we can begin to revisit ideas engaged by Rousseau and other philosophers on man in a state of nature. How can we transcend anarchy? Anarchy can be conceived of as a kind of social network phenomenon, and society and social order can also be conceived of as a social network phenomenon.
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We are thus at a moment where a leap forward in the methodology for the study of social networks has been made, firstly by building on past work. But secondly, we are at a moment where — because of modern telecommunications technologies and other innovations — people are leaving digital traces of where they are, who they are interacting with, and what they are saying or even thinking. All of these types of data can be captured by the deployment of what I call “massive passive” technologies and used to engage social science questions in a way that our predecessors could only dream of. We have vast amounts of data that can be reapplied to investigate fundamental questions about social organization and about morality and other concerns that have perplexed us forever.
We have had advances in methods, we have had advances in data. We have also had advances in ideas. People are beginning to think more creatively about what it means to have these kinds of higher-order structures. Since the late 1990s and into the 2000s science more generally has been engaged in what I call the “assembly project” of modern science. . . .
Neuroscientists are beginning to think: okay, well, we understand a lot about neurons, but how do they interconnect to form brains? Geneticists are saying: at the end of the day, we will have understood all 25,000 (approximately) human genes, and then what? How do we put Humpty Dumpty back together again? How do we reassemble all of the genes and understand how they interact with each other in space and across time? We have seen the recent birth of a new field of biology called systems biology, which seeks to put the parts back together.
And similarly, in social science, there is an increasing interest in the same kind of phenomenon. . . .
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Understanding all of this is what drives me and James Fowler to death right now. And as we have been thinking about it, we have come up with some initial simple ideas, and some initial intriguing and very novel empirical observations. The simple ideas are the following: it is critical when you think of networks to think about their dynamics. A lot of times, people fail to understand networks because they focus on the statics. They think about topology; they think about the architecture of the network. They think about how people are connected, which is of course incredibly important and not easy to understand either. While on the one hand the topology can be understood or seen as fixed or existing, on the other hand this topology is itself mutable and changing and intriguing, and the origin of this topology and its change is itself a difficult thing.
But here is something else: Once you have recognized that there is a topology, the next thing you must understand is that there can be a contagion as well — a kind of process of flow through the network. Things move through it, and this has a different set of scientific underpinnings altogether. Understanding how things flow through the network is a different challenge from understanding how networks form or evolve. It is the difference between the formation and the operation of the network, or the difference between its structure and its function. Or, if you see the network as a kind of super-organism, it is the difference between the anatomy and the physiology of the super-organism, of the network. You need to understand both. And they both interconnect and affect each other, just as in our bodies our anatomy and our physiology are interrelated.
This is what James and I are tackling right now; we have started with several projects that seek to understand the processes of contagion, and we have also begun a body of work looking at the processes of network formation — how structure starts and why it changes. We have made some empirical discoveries about the nature of contagion within networks. And also, in the latter case, with respect to how networks arise, we imagine that the formation of networks obeys certain fundamental biological, genetic, physiological, sociological, and technological rules.
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We are interested not in biological contagion, but in social contagion. One possible mechanism is that I observe you and you begin to display certain behaviors that I then copy. For example, you might start running and then I might start running. Or you might invite me to go running with you. Or you might start eating certain fatty foods and I might start copying that behavior and eat fatty foods. Or you might take me with you to restaurants where I might eat fatty foods. What spreads from person to person is a behavior, and it is the behavior that we both might exhibit that then contributes to our changes in body size. So, the spread of behaviors from person to person might cause or underlie the spread of obesity.
A completely different mechanism would be for there to be not a spread of behaviors, but a spread of norms. I look at the people around me and they are gaining weight. This changes my idea, consciously or subconsciously, about what is an acceptable body size. People around me who start gaining weight reset my expectations about what it means to be overweight or thin, and this is what spreads from person to person: a norm. It is a kind of meme (but it is not quite a meme) that goes from person to person.
In our empirical work so far, we have found substantial evidence for the latter mechanism, the spread of norms, more than the spread of behaviors. It is a bit technical, but I will tell you why we have some evidence for norms. In our empirical work on obesity, we found two lines of suggestive evidence for a spread of norms. The first line of evidence caught everyone’s attention, and frankly it caught our attention when we noted it. It showed that it did not matter how far away your social contacts were; if they gained weight, it caused you to gain weight. This was the case whether your friend lived next door, ten miles away, 100 miles away, or 1000 miles away. Geographic distance did not matter to the obesity effect, the interpersonal effect.
Another finding from looking at the spread of smoking behavior was that if you stop smoking, it makes me stop smoking and there is a spread of smoking cessation behavior, which itself is something we are investigating. Pertinent for the present purpose, however, is that, after taking into account the spread of smoking cessation behavior, it did not efface the spread of obesity. In other words, accounting for one particular behavior, smoking cessation (which is known to increase weight at the individual level), did not undo the spread-of -obesity effect. This is an example in which it is not a spread of a behavior that causes the spread of obesity. This finding, coupled with the finding regarding the lack of decay with geographic distance, suggests to us that it is a norm rather than a behavior that is spreading.
Why? Because for a behavior to spread, typically, you and I would have to be together. We would have to go running together, share meals together, or copy each other’s behavior in some way. And that should decay with geographic distance because the farther away you are, the less time we can spend together. But a norm can fly through the ether. I might see you once a year and see that you have gained a tremendous amount of weight, which resets my idea about what an acceptable body size is. And minimal contact might be enough.
If I go see my brother Dimitri for Thanksgiving, no matter how much food we eat, no matter how much we share the behavior of eating, it will not change my weight that one day. But if I see him and he has gained a lot of weight, it can change my idea about what an acceptable body size is and, in that way, the spread of the norm can cause the spread of obesity.
Clothing fashions spread in our society. One way this can happen is you see people that reset your idea of what is fashionable. Another is more pragmatic. I take you shopping and we pick something out together. I say, “Oh, I heard about a new store,” whatever. Those are two different ways in which fashions might spread.
We also have found in our work that things beyond obesity and smoking cessation spread in networks. Happiness spreads in networks. If your friend’s friend becomes happy, it ripples through the network and can make you happy. We see clusters of happy and unhappy individuals in the social network like blinking lights in this complex fabric that is made up of people where some people are happy and some people are unhappy and there is a kind of gray zone between them. There is an ongoing kind of equilibrium that is reached in this social space. We have found that depression can spread, and drinking behaviors can spread, and the kinds of foods people choose to eat can spread (a taste for tastes can spread, as one of my graduate students is studying). All of this using the initial Framingham Heart Study Social Network data set.
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Incidentally, we are not claiming that the fact that obesity might spread through social networks — or that the social network phenomenon might be relevant to the obesity epidemic — is the only explanation for the epidemic. No doubt there are many explanations. Those explanations, incidentally, are not genetic. Our genes haven’t changed in the last 30 years.
The real explanations for the obesity epidemic are exclusively socio-environmental — things having to do with the increasing consumption of calories in our society: food is becoming cheaper, the composition of food is changing, there is increasing marketing of foodstuffs and the like. Also, clearly, there has been a change of rate at which people burn calories due to an increase in sedentary lifestyles, the design of our suburbs, and a whole host of such explanations.
We are not claiming that such explanations are not relevant. No doubt they are all part of the obesity epidemic. We are just saying that networks have this fascinating property whereby they magnify whatever they are seeded with. And so if you can get something going in a networked population like obesity, it can spread.
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We also mention in our paper in the New England Journal the possible relevance of so-called “mirror neurons,” which is another mechanism which I didn’t touch on earlier. One possibility besides biological contagion is that by watching you exhibit certain kinds of behaviors like eating or running, I start to copy those behaviors mentally in a mirror-neuron kind of way. And this facilitates my exhibiting the same behavior.
It is actually quite complicated to know how to exploit these network phenomena in a situation like the one we have been discussing because if you have a lot of people of one body type and you introduce somebody of a different body type, it is unclear who will influence whom. The thin person might gain weight, or the overweight people might lose weight. Or both. It is a very complicated dynamic, which again requires a kind of deployment of a certain kind of data and methods to begin to understand.
I should also stress something very important, which is that James Fowler’s and my primary focus is not obesity, it is networks. Obesity happens to be an incredibly important public health problem and was something very important to study, above all because it showed how something people might not have thought of as spreading in social networks could. If we had shown, for example that fashion spread in social networks, that might be much less interesting to people. But if you can show that something like obesity or happiness or even goodness spreads in social networks, you are on new terrain.
Incidentally, some of these things also touch on very old philosophical and social science concerns, as I mentioned earlier, because they raise questions about free will. If my behaviors and my thoughts are determined not just by my own volition, but are determined by the behaviors and thoughts of other people to whom I am connected, and are even determined by the behaviors and thoughts of other people who I do not know and who are beyond my social horizon but who are connected to people to whom I am connected, it speaks to the issue of free will. Are my thinking and my behavior truly free, or are they constrained because I am part of a social network? To the extent that I am part of this human super-organism, does that reduce my individuality? And does this give us more or less insight into human behavior?
Because we are talking about networks of human beings rather than networks of neurons or computers, it is the case that I am not just plunked down in a network that is determined by some kind of exogenous physical law. There is no doubt that the topology obeys certain biological and psychological rules and laws, but it is also true that I can choose who my friends are and say, “You know, I don’t like these friends; I am going to pick new friends,” and in turn choose new friends.
That is, your desires and ideas can influence the structure of your network. For example, if you have ideas that foster a certain kind of ties, those ties in turn foster and support certain kinds of ideas. You can imagine a circumstance in which certain kinds of ideologies can survive and offer certain kinds of advantages because they bind the group together, or tear it apart, in particular kinds of ways. We have been thinking a little bit about this in terms of groups of people that seem to evince what would appear to be self-destructive behaviors, but our thoughts in this regard are still very preliminary.
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. . . . We have talked about the flow of obesity through a network, we have talked about the flow of happiness through a network, we have talked about the flow of smoking cessation through a network, we have talked about the flow of fashions through a network. Now we are talking about the flow of tastes in privacy through the network. And tastes in all kinds of other things, like music, movies, or books, or a taste in food. Or a flow of altruism through the network. All of these kinds of things can flow through social networks and obey certain rules we are seeking to discover.
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To read the entire transcript or view the video on Edge, click here. For previous Situationist posts discussing the work of Christakis and Fowler, see “Common Cause: Combating the Epidemics of Obesity and Evil,” and “Situational Obesity, or, Friends Don’t Let Friends Eat and Veg.” For Situationist posts discussing the situational sources of obesity, click here.