THE idea that everyone on the planet is separated by only an average of six degrees sounds a little too elegant to be true, and yet it seems to hold. The first experiment to confirm this came in the 1960s when psychologist Stanley Milgram asked several hundred people in Nebraska to send a letter to a stranger in Boston via someone they knew. On average, it took . The experiment was repeated in 2002 by sociologist Duncan Watts on a global scale using email, with the . The world really is that small.
In their new book Connected, sociologist and physician and political scientist identify another immutable property of social networks that sits nicely alongside Milgram鈥檚: behaviours, habits and other traits 鈥渞ipple鈥� along chains of friends and are contagious at up to three degrees of separation. Thus, my actions and moods 鈥� whether I鈥檓 happy or depressed, fat or thin, whether I smoke, even whether I vote in elections 鈥� affect my friends, my friends鈥� friends and my friends鈥� friends鈥� friends. Thereafter my influence fades away.
What is it about human society that gives it such an enduring structure? Why not seven degrees of separation, or four degrees of contagion? Christakis and Fowler do not quite answer this, but they provide an illuminating account of the pervasive and often bizarre qualities of social networks which, they claim, cannot be understood in terms of the behaviour or psychology of individuals within them. Rather, the networks have a life of their own. We like to think we are largely in control of our day-to-day lives, yet most of what we do, and even the way we feel, is significantly influenced by those around us 鈥� and those around them, and those around them.
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Much of what is covered in Connected sounds obvious at first, an impression not helped by the authors鈥� tendency to apply the tools of network science to issues that do not fully merit them. A main conclusion of the chapter on love 鈥� that people tend to meet their long-term partners through friends and families rather than randomly 鈥� is hardly revelatory. Dig a little deeper, though, and things are anything but obvious. Why, for example, are emotional states so much more contagious when passed on by friends and relatives of the same gender? Why do men married to white women suffer a significant decline in physical and psychological health when their spouse dies while men married to black women do not? The authors excel at drawing out the devil in the detail: their explanations of how the architecture of networks dictates their dynamics are compelling.
All this has profound implications, both for our ideas about autonomy and free will and for public policy, especially in matters of social inequality and health 鈥� something Christakis and Fowler flag up but might have given more attention. Given how triggers for illness (smoking and eating habits, for example) and for well-being (positive moods) radiate through social networks, should health authorities consider the effect of treatments on whole networks rather than on individuals alone? More particularly, given that well-connected people are likely to pass on health benefits to a greater number of people, should medical interventions be directed preferentially at social 鈥渉ubs鈥�?
鈥淪hould medical interventions be directed preferentially at people who are social 鈥榟ubs鈥�?鈥�
It is a difficult question, and ultimately a moral one. If anything, we should be helping rather than penalising those who are socially isolated as they are likely to be suffering more already. Yet as Connected demonstrates, targeting centrally placed individuals can improve the way people eat and reduce risky sexual behaviours. We should be open to the idea of using networks to address other social ills too, such as inequality and crime.
The science of social networks is alluring because it gives us another way of seeing the world. We will never fully understand people without understanding the links between them, the authors say. 鈥淥ur connections matter much more than the colour of our skin or the size of our wallets鈥� When we lose [them], we lose everything.鈥�
Little, Brown
