This link has been bookmarked by 17 people . It was first bookmarked on 26 Feb 2008, by Will Richardson.
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18 Feb 09
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Christakis notes that he is "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.
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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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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.
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I began to see in a very real way that the illness of the person dying was affecting the health status of other individuals in the family. And I began to see this as a kind of non-biological transmission of disease — as if illness or death or health care use in one person could cause illness or death or health care use in other people connected to him. It wasn't an epidemic transmission of a germ; something else was happening. This is a very basic observation about what I now call “interpersonal health effects,”
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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
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Georg Simmel
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people like Mark Granovetter, Stan Wasserman, Ron Burt, and others
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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.
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We can start with the tiny case of a man and a woman — a pair of individuals — one of whom is sick and the other of whom cares (partly from altruistic reasons) for that person. Stepping back to see them not as individuals, but focusing on the tie that connects them as the object of inquiry, we see that they are embedded in larger sets of such networks, which forces us to engage with a set of fundamental social scientific and philosophical problems — in fact moral problems — that people have been concerned with for millennia.
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These methods incidentally were built on some efforts by very well-known Hungarian mathematicians who studied a branch of mathematics known as topology, which itself has an interesting and old history stretching back to Euler. Beginning in the 1990s, there was a kind of resurrection of network science, initially caused by a group of physicists and mathematicians who were actually tackling problems in other domains. For instance, people interested in networks of genes, or cellular networks, or networks of neurons, like my colleague Laszlo Barabasi.
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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.
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Since the late 1990s and into the 2000s science more generally has been engaged in what I call the “assembly project” of modern science.
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How do we reassemble all of the genes and understand how they interact with each other in space and across time?
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And similarly, in social science, there is an increasing interest in the same kind of phenomenon.
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We have, for example, consciousness, which cannot be understood by studying neurons. Consciousness is an emergent property of neuronal tissue. And we can imagine similarly certain kinds of emergent properties of social networks that do not inhere in the individuals — properties that arise because of the ties between individuals and because of the complexity of those ties.
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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.
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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.
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Things move through it
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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.
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we have started with several projects that seek to understand the processes of contagion
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So we have been investigating both what causes networks to form and how networks operate.
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It also includes the basic idea that there is something contagious that is spreading from person to person.
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We wanted to study whether this was the case. Could obesity flow through networks? Could one person's body type actually influence the body type of others around him, and around them, and around them, in a cascade effect?
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How did we do that? We needed to come up with a source of data that contained information about people's position in a network, the architecture of their ties — who they knew and who those people knew and who those people knew and so forth. We also needed a source of data on people's weight and other information about them. And we needed it for a long period of time with repeated observations on these people.
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What we found when we did this study is that weight gain in your friends makes you gain weight and weight gain among people beyond what we call your “social horizon” ripples through the network and affects you.
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To us, it is a very, very fundamental observation that things happening in a social space beyond your vision — events that occur or choices that are made by people you don't know — can cascade in a conscious or subconscious way through a network and affect you. This is a very profound and fundamental observation about the operation of social life, which we initially examined while looking at obesity.
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Moreover, people beyond those to whom you were directly tied also influenced your weight, people up to three degrees removed from you in the network. And, incidentally, we found that weight loss obeys the same properties and spreads similarly through the network.
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In the case of obesity, we formulated a variety of ideas
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One possible mechanism is very simple, which is biological contagion.
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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.
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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.
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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.
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Geographic distance did not mater to the obesity effect, the interpersonal effect.
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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.
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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.
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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.
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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.
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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).
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This is the difference between ideology and norms. People see these images of super models, but they might be less influenced by them than by the actions and appearance of the people immediately around them.
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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.
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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.
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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.
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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.
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When it comes to the internet, we are no longer merely talking about networks of computers or of networks of people who are in communication with each other, but we are talking about truly social networks, such as Facebook and MySpace and Friendster and LinkedIn.
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We have trawled through this large social network and grabbed information about people in the network, and their social ties, as is available on Facebook — for example, information having to do with their tastes, with the people with whom they appear in photographs, and so on. For example, a person might have an average of 100 or 200 friends on Facebook, but they might only appear in photographs with 10 of them. We would argue that appearing in a photograph constitutes a different kind of social tie than a mere nomination of friendship.
By exploiting these kinds of data and a variety of computer science technologies, we have been able to build a network that changes across time and to trace the flow of tastes through the network (for instance, how as I start listening to a particular kind of music, you start listening to a particular kind of music). We have been able to study homophilic properties — the idea that birds of a feather flock together. How and why do people form unions? Do they depend upon particular attributes, tastes, and the like? We have been able to study how these types of things — both the topology of the network and the things that flow through the network — change over time.
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But then we realized that, in addition to its conceptual importance, we could treat privacy as a taste. And we saw that the taste for privacy flowed through the network so that if I adopt privacy settings on Facebook, the people to whom I am connected will be more likely to adopt privacy settings.
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So here we observe yet another phenomenon. 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.
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12 Sep 08
gabriela ortizmichelvia sephoria "an article on spreadable chronic diseases like obesity"
no pude escuchar el video... es un desmadre porque no lo carga desde antes...
pero abajo está doblado y me parece muy interesante. Este Christakis es médico y trabajaba con enfermos ter -
11 May 08
zpinheadBut it turns out that all kinds of things, many of them quite unexpected, can flow through social networks, and this process obeys certain rules we are seeking to discover. We’ve been investigating the spread of obesity through a network, the spread of
socialnetworks social_networks networking SecondLife groups identity
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24 Mar 08
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02 Mar 08
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Recently, Harvard professor and sociologist Nicholas Christakis has shown that there's more to think about regarding social networks such as Facebook, MySpace, Flickr, and Twitter than considerations of advertising and revenue models.
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Christakis notes that he is "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.
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Or you might start eating certain fatty foods and I might start copying that behavior and eat fatty foods.
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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."
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In a page one story in The New York Times last summer ("Find Yourself Packing It On? Blame Friends" 7.26.07), Gina Kolata noted:
Obesity can spread from person to person, much like a virus, researchers are reporting today. When one person gains weight, close friends tend to gain weight, too.
Their study, published in The New England Journal of Medicine, involved a detailed analysis of a large social network of 12,067 people who had been closely followed for 32 years, from 1971 to 2003.
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The answer, the researchers report, was that people were most likely to become obese when a friend became obese. That increased a person’s chances of becoming obese by 57 percent. There was no effect when a neighbor gained or lost weight, however, and family members had less influence than friends.
It did not even matter if the friend was hundreds of miles away, the influence remained. And the greatest influence of all was between close mutual friends. There, if one became obese, the other had a 171 percent increased chance of becoming obese, too. ...
Christakis, along with his colleague James Fowler, "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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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?
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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.
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In addition to my training in social science, I was trained as a hospice doctor. When I was at the University of Chicago (until 2001), I had a very special clinical practice that involved taking care of people in their own homes
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I began to see in a very real way that the illness of the person dying was affecting the health status of other individuals in the family. And I began to see this as a kind of non-biological transmission of disease — as if illness or death or health care use in one person could cause illness or death or health care use in other people connected to him. It wasn't an epidemic transmission of a germ; something else was happening. This is a very basic observation about what I now call “interpersonal health effects,” but as I began to have more and more clinical experience with such patients, I began to broaden the focus. I became interested not just in dyadic transmission of illness and illness burden, but also hyper-dyadic transmission.
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Beginning in the 1990s, there was a kind of resurrection of network science, initially caused by a group of physicists and mathematicians who were actually tackling problems in other domains. For instance, people interested in networks of genes, or cellular networks, or networks of neurons, like my colleague Laszlo Barabasi. For example, if we have a simple worm that has 200 neurons, can we map all of the connections between the 200 neurons and thereby understand how the worm learns, or how it behaves? Can we understand learning and behavior not by studying the neurons, but by studying the interconnection between neurons?
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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.
-
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
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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.
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Why? Because for a behavior to spread, typically, you and I would have to be together.
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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.
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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.
-
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.
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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?
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01 Mar 08
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29 Feb 08
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28 Feb 08
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27 Feb 08
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26 Feb 08
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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.
-
Some level of altruism is required for networks to emerge.
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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.
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Again, the study of social networks is part of this assembly project, part of this effort to understand how you can then have the emergence of order and the emergence of new phenomena that do not inhere in the individuals.
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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 statistics. 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.
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To us, it is a very, very fundamental observation that things happening in a social space beyond your vision — events that occur or choices that are made by people you don't know — can cascade in a conscious or subconscious way through a network and affect you.
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