The Spread of Happiness
Despite the biological and psychological evidence for emotional mimicry, and the numerous cases of MPI arising from epidemic anxiety, until recently little was known about the precise role of social networks in the spread of emotions. Yet, the MPI cases suggest that emotions spread far and wide, flowing through social-network ties from person to person to person, and that there should be a normal analogue to this pathological phenomenon. Indeed, there can be waves of emotions in the vast fabric of human social relationships, so that people in particular locations in the social network have one emotional experience, and others elsewhere who come under different influences have a different experience altogether.
Strangely, while researchers in diverse fields, including medicine, economics, psychology, neuroscience, and evolutionary biology, have identified a broad range of stimuli of individual human happiness, they have not addressed a key (perhaps the key) determinant: the happiness of others. It may be obvious that our friends and family can make us happy, but before we undertook our own investigation, no one had ever explored how happiness can spread through social networks from person to person to person.
We became curious about this. We were particularly interested in determining whether the spread of emotions occurred not just between you and your friends (dyadic spread) but also between you and your friends’ friends, and their friends, and beyond (hyper-dyadic spread). How far did emotions travel in the network? And were there geographic or temporal constraints on the spread?
Our first step in answering these questions was to assemble a data set that had measures of emotions and social connections over time. (We discuss that process in chapter 4.) We then created a graph of the social network of happiness, as shown in plate 1. This illustration shows ties among siblings, friends, and spouses in a sample drawn from 12,067 people originally from Framingham, Massachusetts, in the year 2000, along with their levels of happiness. No one had ever plotted such a graph before. One thousand twenty people are represented, and each node is colored on a spectrum from blue (unhappy) to yellow (happy) according to the subject’s level of happiness. Looking at this image suggests two observations. First, unhappy people cluster with unhappy people in the network, and happy people cluster with happy people. Second, unhappy people seem more peripheral: they are much more likely to appear at the end of a chain of social relationships or at the edge of the network.26
Clustering of this kind in social networks can arise from a variety of processes. Happy people might choose each other as friends or be exposed to the same environments that cause them all to be happy at the same time. But our analyses allowed us to adjust for these effects. And we found that clustering is also due to the causal effect of one person’s happiness on another’s. Mathematical analyses of the network suggest that a person is about 15 percent more likely to be happy if a directly connected person (at one degree of separation) is happy. And the spread of happiness doesn’t stop there. The happiness effect for people at two degrees of separation (the friend of a friend) is 10 percent, and for people at three degrees of separation (the friend of a friend of a friend), it is about 6 percent. At four degrees of separation, the effect peters out. Here we have our first evidence of the Three Degrees of Influence Rule. Emotions (and, as we will see later, norms and behaviors) spread in social networks from person to person to person, but they do not spread to everyone. Just as a ripple in a pond eventually fades away, so too does the ripple of an individual’s happiness fade through the social network.
At first glance, these effects may not seem very significant. But compare them to the effect of having a higher income. An extra $5,000 in 1984 dollars (which corresponds to about $10,000 in 2009 dollars) was associated with only a 2 percent increased chance of a person being happy. So, having happy friends and relatives appears to be a more effective predictor of happiness than earning more money. And the amazing thing is that even people who are three degrees removed from you, whom you may have never met, can have a stronger impact on your personal happiness than a wad of hundreds in your pocket. Being in a particular spot in a social network, exposed to people with particular feelings, has important implications for your life.
It is well known that having more friends and relatives is much more likely to put a smile on your face than having more cash.27 But past research had never considered why friends matter so much. There are at least two possibilities. First, the existence of the social relationship itself may improve your happiness—this is a structural effect of the network on you (the second rule of social networks described in chapter 1). As we discuss in chapter 7, we are hardwired to seek out social relationships, so it is not surprising that we feel pleasure or reward when we spend time with friends and family. Second, friends and relatives make us susceptible to emotional contagion, so our friends’ emotional states affect our own (the third rule of social networks).
While both of these mechanisms probably contribute to people’s happiness, our evidence suggests that contagion may be the more important of the two. We found that each happy friend a person has increases that person’s probability of being happy by about 9 percent. Each unhappy friend decreases it by 7 percent. So if you were simply playing the averages, and you didn’t know anything about the emotional state of a new person you just met, you would probably want to be friends with her. She might make you unhappy, but there is a better chance she will make you happy. This helps to explain why past researchers have found an association between happiness and the number of friends and family. But once we control for the emotional states in one’s friends, we find that having more friends is not enough—having more happy friends is the key to our own emotional well-being.
This does not mean that the structure of the social network is unimportant. Amazingly, it is not just the number of dyadic ties that has an impact; the number of hyperdyadic ties also influences a person’s happiness. When we measured the centrality of each person in the social network, we found that people with more friends of friends were also more likely to be happy. And, more remarkably, this was true even among people who had the same number of direct social relationships. This means that the more friends your friends have (regardless of their emotional state), the more likely you are to be happy.
One might wonder if there is a chicken-and-egg problem here. After all, it is possible to imagine that when we become happier, we tend to attract more friends, and more friends who have lots of friends. This would mean that happiness is driving the network rather than the other way around. But when we examined how the network changes over time, we found that happy people do not tend to become more central. So having a wide social circle can make you happy, but being happy does not necessarily widen your social circle. Being located in the middle of the network leads to happiness rather than the other way around. The structure of your network and your location in it matter.
Given how important direct interaction seems to be for emotional contagion to occur, we also theorized that the effect of the happiness of your social contacts on your emotional state should depend on how near or far they are. The idea is that people who live nearby are more likely to be in contact and therefore more likely to pick up on each others’ moods. Geographic distance can be used as a proxy for frequency of social interaction. In our study, about one in three people live within a mile of their closest friend, but there is a lot of variation, and some friends live thousands of miles apart. We found that when a friend who lives less than a mile away becomes happy, it can increase the probability that you are happy by 25 percent. In contrast, the happiness of a friend who lives more than a mile away has no effect. Similarly, if your spouse lives with you and he or she becomes happy, then your probability of happiness goes up, but spouses who do not live together (because they are separated) have no effect on each other. A happy sibling who lives less than a mile away increases your chance of happiness by 14 percent, but more distant siblings have no significant effect. And happy next-door neighbors also increase your chance for happiness, while neighbors who live farther away (even on the same block) have no significant effect.
All these findings suggest the importance of proximity among people whose emotions influence each other, and the impact of immediate neighbors suggests that the spread of happiness may depend as much on frequent face-to-face interaction as on deep personal connections. While in this case we are considering the spread of a dis-positional state of some duration, these findings are also in keeping with the work on facial mimicry we discussed earlier.
Happiness is thus not merely a function of individual experience or choice; it is also a property of groups of people. Changes in individual happiness can ripple through social connections and create large-scale patterns in the network, giving rise to clusters of happy and unhappy individuals. Since our work was published, similar results on the spread of happiness have been observed in a sample of ten thousand rural Chinese villagers.28 Although we could not observe what causes happiness to spread, a variety of mechanisms are conceivable. Happy people may share their good fortune (e.g., by being pragmatically helpful or financially generous to others), change their behavior toward others (e.g., by being nicer or less hostile), or merely exude an emotion that is contagious. Being surrounded by happy people might have beneficial biological effects too. But whatever the mechanism, it seems clear that we need to change the way we think about happiness and other emotions.
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