Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler Flashcards

1
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simplest social network of all: a pair of people, a dyad. 21

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2
Q

How did humans come together to accomplish what they could not do on their own? 39

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3
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if your friend’s friend’s friend gained weight, you gained weight. We discovered that if your friend’s friend’s friend stopped smoking, you stopped smoking. And we discovered that if your friend’s friend’s friend became happy, you became happy. 44

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4
Q

A network of humans has a special kind of life of its own. 55

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5
Q

we began to think of them as a kind of human superorganism. 61

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6
Q

Just as brains can do things that no single neuron can do, so can social networks do things that no single person can do. 67

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7
Q

For decades, even centuries, serious human concerns, such as whether a person will live or die, be rich or poor, or act justly or unjustly, have been reduced to a debate about individual versus collective responsibility. 68

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8
Q

Scientists, philosophers, and others who study society have generally divided into two camps: those who think individuals are in control of their destinies, and those who believe that social forces (ranging from a lack of good public education to the presence of a corrupt government) are responsible for what happens to us. 70

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9
Q

believe that our connections to other people matter most, 74

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10
Q

To know who we are, we must understand how we are connected. 77

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11
Q

Notions of collective guilt and collective revenge that underlie cascades of violence seem strange only when we regard responsibility as a personal attribute. Yet in many settings, morality resides in groups rather than in individuals. 106

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12
Q

Two-thirds of the acts of interpersonal violence in the United States are witnessed by third parties, and this fraction approaches three-fourths among young people.4 108

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13
Q

In the United States, 75 percent of all homicides involve people who knew each other, often intimately, prior to the murder. 116

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14
Q

Social-network ties can—and, as we will see, usually do—convey benefits that are the very opposite of violence. 136

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15
Q

Social networks spread happiness, generosity, and love. 144

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16
Q

If each person acts independently, then your house will surely be destroyed. Fortunately, this does not happen because a peculiar form of social organization is deployed: the bucket brigade. 154

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17
Q

It’s amazing to be able to increase the effectiveness of human beings by as much as an order of magnitude simply by arranging them differently. 161

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18
Q

A group can be defined by an attribute (for example, women, Democrats, lawyers, long-distance runners) or as a specific collection of individuals to whom we can literally point (“those people, right over there, waiting to get into the concert”). 167

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19
Q

A social network is altogether different. While a network, like a group, is a collection of people, it includes something more: a specific set of connections between people in the group. These ties, and the particular pattern of these ties, are often more important than the individual people themselves. They allow groups to do things that a disconnected collection of individuals cannot. 169

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20
Q

A company of one hundred soldiers is typically organized into ten tightly interconnected squads of ten. 176

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21
Q

The telephone tree also vastly reduces the number of steps it takes for information to flow among people in the group, minimizing the chance that the message will be degraded. 194

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22
Q

An article in the Los Angeles Times from 1957, for example, describes the use of a phone tree to mobilize amateur astronomers, as part of the “Moonwatch System” of the Smithsonian Astrophysical Observatory, to track American and Russian satellites.8 197

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23
Q

A network community can be defined as a group of people who are much more connected to one another than they are to other groups of connected people found in other parts of the network. 214

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24
Q

Four different ways to connect one hundred people. Each circle (“node”) represents a person, and each line (“tie”) a relationship between two people. Lines with arrows indicate a directed relationship; in the telephone tree, one person calls another. Otherwise, ties are mutual: in the bucket brigade, full and empty buckets travel in both directions; in military squads, the connections between the soldiers are all two-way. 218

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25
Q

a social network is an organized set of people that consists of two kinds of elements: human beings and the connections between them. 221

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26
Q

On average, each student is connected to six other close friends, but some students have only one friend, and others have many. 226

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27
Q

having better-connected friends literally moves you away from the edges and toward the center of a social network. 231

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28
Q

In this natural network of close friendships among 105 college students living in the same dormitory, each circle represents a student, and each line a mutual friendship. 236

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29
Q

A network’s shape, also known as its structure or topology, is a basic property of the network. 241

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30
Q

Visualization software tries to show this in two dimensions and to reveal the underlying topology by putting the most tangled buttons in the center and the least connected ones on the edges. 253

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31
Q

First, there is connection, which has to do with who is connected to whom. 262

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32
Q

Second, there is contagion, which pertains to what, if anything, flows across the ties. 268

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33
Q

RULE 1: WE SHAPE OUR NETWORK 274

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34
Q

homophily, the conscious or unconscious tendency to associate with people who resemble us (the word literally means “love of being alike”). 275

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35
Q

we also choose the structure of our networks in three important ways. First, we decide how many people we are connected to. 278

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36
Q

Second, we influence how densely interconnected our friends and family are. 280

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37
Q

third, we control how central we are to the social network. 282

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38
Q

three thousand randomly chosen Americans. And we found that the average American has just four close social contacts, with most having between two and six. Sadly, 12 percent of Americans listed no one with whom they could discuss important matters or spend free time. At the other extreme, 5 percent of Americans had eight such people. 294

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39
Q

Sociologist Peter Marsden has called this group of people that we all have a “core discussion network.” 298

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40
Q

a national sample of 1,531 Americans studied in the 1980s, he found that core-discussion-network size decreases as we age, that there is no overall difference between men and women in core-network size, and that those with a college degree have core networks that are nearly twice as large as those who did not finish high school.9 299

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41
Q

this relationship is transitive—the three people involved form a triangle. 306

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42
Q

Those with high transitivity are usually deeply embedded within a single group, while those with low transitivity tend to make contact with people from several different groups who do not know one another, making them more likely to act as a bridge between different groups. 308

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43
Q

typical American, the probability that any two of your social contacts know each other is about 52 percent. 310

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44
Q

RULE 2: OUR NETWORK SHAPES US 322

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45
Q

Our place in the network affects us in turn. A person who has no friends has a very different life than one who has many. 322

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46
Q

Transitivity can affect everything from whether you find a sexual partner to whether you commit suicide. 333

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47
Q

Being more central makes you more susceptible to whatever is flowing within the network. 342

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48
Q

your centrality affects everything from how much money you make to whether you will be happy. 346

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49
Q

RULE 3: OUR FRIENDS AFFECT US 347

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50
Q

Students with studious roommates become more studious. 354

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51
Q

RULE 4: OUR FRIENDS’ FRIENDS’ FRIENDS AFFECT US 356

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52
Q

hyperdyadic spread, or the tendency of effects to spread from person to person to person, beyond an individual’s direct social ties. 363

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53
Q

Psychologist Stanley Milgram’s famous sidewalk experiment illustrates the importance of reinforcement from multiple people.12 On two cold winter afternoons in New York City in 1968, Milgram observed the behavior of 1,424 pedestrians as they walked along a fifty-foot length of street. He positioned “stimulus crowds,” ranging in size from one to fifteen research assistants, on the sidewalk. On cue, these artificial crowds would stop and look up at a window on the sixth floor of a nearby building for precisely one minute. There was nothing interesting in the window, just another guy working for Milgram. The results were filmed, and assistants later counted the number of people who stopped or looked where the stimulus crowd was looking. While 4 percent of the pedestrians stopped alongside a “crowd” composed of a single individual looking up, 40 percent stopped when there were fifteen people in the stimulus crowd. Evidently, the decisions of passersby to copy a behavior were influenced by the size of the crowd exhibiting it. 382

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54
Q

While one person influenced 42 percent of passersby to look up, 86 percent of the passersby looked up if fifteen people were looking up. 391

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55
Q

a stimulus crowd of five people was able to induce almost as many passersby to look up as fifteen people did. 392

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56
Q

RULE 5: THE NETWORK HAS A LIFE OF ITS OWN 394

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57
Q

1986 World Cup in Mexico. In this phenomenon, originally called La Ola (“the wave”), 401

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58
Q

waves usually rolled in a clockwise direction and consistently moved at a speed of twenty “seats per second.”13 404

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59
Q

there is no central control of the movement of the group, but the group manifests a kind of collective intelligence that helps all within it to flee or deter predators. 413

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60
Q

This behavior does not reside within individual creatures but, rather, is a property of groups. 414

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61
Q

the flock’s collective choice is better than an individual bird’s would be.14 416

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62
Q

social networks have emergent properties. Emergent properties are new attributes of a whole that arise from the interaction and interconnection of the parts. 419

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63
Q

Stanley Milgram masterminded another, much more famous experiment showing that people are all connected to one another by an average of “six degrees of separation” 425

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64
Q

small-world effect originally characterized by de Sola Pool and Kochen, 431

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65
Q

in 2002, physicist-turned-sociologist Duncan Watts and his colleagues Peter Dodds and Roby Muhamad decided to replicate Milgram’s experiment on a global scale using e-mail as the mode by which people communicated.16 434

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66
Q

spread of influence in social networks obeys what we call the Three Degrees of Influence Rule. 443

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67
Q

Everything we do or say tends to ripple through our network, having an impact on our friends (one degree), our friends’ friends (two degrees), and even our friends’ friends’ friends (three degrees). Our influence gradually dissipates and ceases to have a noticeable effect on people beyond the social frontier that lies at three degrees of separation. 443

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68
Q

we are influenced by friends within three degrees but generally not by those beyond. 446

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69
Q

There are three possible reasons our influence is limited. First, like little waves spreading out from a stone dropped into a still pond, the influence we have on others may eventually peter out. 451

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70
Q

We call this the intrinsic-decay explanation. 456

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71
Q

Second, influence may decline because of an unavoidable evolution in the network that makes the links beyond three degrees unstable. Ties in networks do not last forever. Friends stop being friends. 456

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72
Q

We call this the network-instability explanation. 461

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73
Q

Third, evolutionary biology may play a part. As we will discuss in chapter 7, humans appear to have evolved in small groups in which everyone would have been connected to everyone else by three degrees or less. 462

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74
Q

we may not be able to influence people four degrees removed from us because, in our hominid past, there was no one who was four degrees removed from us. We call this the evolutionary-purpose explanation. 465

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75
Q

the observation that there are six degrees of separation between any two people applies to how connected we are, the observation that there are three degrees of influence applies to how contagious we are. 478

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76
Q

properties, connection and contagion, are the structure and function of social networks. They are the anatomy and physiology of the human superorganism. 480

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77
Q

Social networks have value precisely because they can help us to achieve what we could not achieve on our own. 488

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78
Q

a social network is like a commonly owned forest: we all stand to benefit from it, but we also must work together to ensure it remains healthy and productive. 493

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79
Q

two different kinds of inequality in our society: situational inequality (some are better off socioeconomically) and positional inequality (some are better off in terms of where they are located in the network). 499

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80
Q

If we want to understand how society works, we need to fill in the missing links between individuals. 513

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81
Q

“endwara yokusheka,” which means simply, “the illness of laughing.” 539

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82
Q

emotions have a collective and not just an individual origin. How you feel depends on how those to whom you are closely and distantly connected feel. 543

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83
Q

First, we usually have a conscious awareness of our emotions: when we are happy, we know it. 546

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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84
Q

Second, emotions typically affect our physical state: we show how we feel on our faces, in our voices, even in our posture; 546

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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85
Q

Third, emotions are associated with specific neurophysiological activity; if you are shown a scary picture, the flow of blood to structures deep in your brain instantly changes. 548

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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86
Q

Finally, emotions are associated with visible behaviors, like laughing, crying, or shrieking.2 549

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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87
Q

Experiments have demonstrated that people can “catch” emotional states they observe in others over time frames ranging from seconds to weeks.3 550

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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88
Q

When college freshmen are randomly assigned to live with mildly depressed roommates, they become increasingly depressed over a three-month period.4 551

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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89
Q

When waiters are trained to provide “service with a smile,” their customers report feeling more satisfied, and they leave better tips.5 553

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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90
Q

Given the organization of early hominids into social groups, the spread of emotions served an evolutionarily adaptive purpose.6 Early humans had to rely on one another for survival. 559

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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91
Q

The development of emotions in humans, the display of emotions, and the ability to read the emotions of others helped coordinate group activity by three means: facilitating interpersonal bonds, synchronizing behavior, and communicating information. 563

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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92
Q

Emotions and emotional contagion probably first arose to facilitate mother-infant pair bonding and then evolved to extend to kin members and ultimately to nonkin members. 565

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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93
Q

positive emotions may work especially well to increase group cohesiveness (“I’m happy; stay with me”) and that negative emotions may work well as communication devices (“I smell smoke; I’m scared”). 573

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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94
Q

Emotions may be a quicker way to convey information about the environment and its relative safety or danger than other forms of communication, and it seems certain that emotions preceded language. 574

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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95
Q

Emotions spread from person to person because of two features of human interaction: we are biologically hardwired to mimic others outwardly, and in mimicking their outward displays, we come to adopt their inward states. 583

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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96
Q

Nowhere do we show our emotions more than on our faces. 587

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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97
Q

Humans have an extraordinary knack for detecting even small changes in facial expressions. This ability is localized in a particular area of the brain and can even be lost, a condition tongue-twistingly known as prosopagnosia. 597

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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98
Q

Even as early as 1759, it was apparent to founding economist and philosopher Adam Smith that conscious thought was one way we could feel for others and hence feel like others: “Though our brother is upon the rack… by the imagination we place ourselves in his situation, we conceive ourselves enduring all the same torments, we enter as it were into his body, and become in some measure the same person with him, and thence form some idea of his sensations, and even feel something which, though weaker in degree, is not altogether unlike them.”8 600

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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99
Q

People imitate the facial expressions of others, then, as a direct result, they come to feel as others do. This is called affective afference, or the facial-feedback theory, 606

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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100
Q

telephone operators are trained to smile when they work, even though the person at the other end of the line cannot see them. This theory also explains why it helps to smile when your heart is breaking. 609

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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101
Q

emotions (and behaviors) contagious may be the so-called mirror neuron system in the human brain.9 Our brains practice doing actions we merely observe in others, as if we were doing them ourselves. 611

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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102
Q

we are always poised to feel what others feel and to do what others do. 620

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Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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103
Q

laughter like the Bukoba outbreak. 627

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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104
Q

When emotions spread from person to person and affect large numbers of people, it is now called mass psychogenic illness (MPI) rather than the old-fashioned and more poetic epidemic hysteria. 627

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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105
Q

A relatively recent example of MPI occurred at the Warren County High School in McMinnville, Tennessee. At the time, the school had 1,825 students and 140 staff members. On November 12, 1998, a teacher believed she smelled gasoline, which caused her to complain of headache, shortness of breath, dizziness, and nausea. Seeing her response, some of her students soon developed similar symptoms. 644

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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106
Q

The diagnosis was epidemic hysteria. 666

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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107
Q

The astonishing reality is that our own anxiety makes us sick, but so does the anxiety of others. 671

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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108
Q

The problem is that while public health professionals often suspect that an outbreak is psychogenic, they feel they have no choice but to conduct an unreasonably thorough investigation because of intense anxiety in the community. 673

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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109
Q

One systematic review of cases of epidemic hysteria identified seventy outbreaks that occurred between 1973 and 1993 and found that 50 percent of them took place in schools, 40 percent in small towns and factories, and only 10 percent in other settings.15 The outbreaks usually involved at least thirty people, and often hundreds. Most outbreaks lasted less than two weeks, but 20 percent lasted more than a month. 680

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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110
Q

For some reason that is not well understood, smells, both real and imagined, are frequent triggers of modern outbreaks of MPI. This may have to do with the well-established connection between olfaction and emotions. 703

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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111
Q

smell and emotion are both regulated by a part of the brain called the orbitofrontal cortex.17 704

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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112
Q

Proust phenomenon, after the author who described a poignant memory inspired by the scent of a cookie. 708

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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113
Q

MPI is a pathological phenomenon, but it takes advantage of a nonpathological process that is fundamental in humans, namely, the tendency to mimic the emotional state of others. 746

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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114
Q

experience-sampling method. This method uses a series of alerts (such as signals sent to a beeper or cell phone) at unexpected times to prompt subjects to document their feelings, thoughts, and actions while they are experiencing them.23 751

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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115
Q

There was a strong association between a player’s own happiness and the happiness of his teammates, independent of the state of the game; further, when a player’s teammates were happier, the team’s performance improved. 768

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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116
Q

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.26 787

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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117
Q

a person is about 15 percent more likely to be happy if a directly connected person (at one degree of separation) is happy. 793

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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118
Q

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. 794

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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119
Q

having happy friends and relatives appears to be a more effective predictor of happiness than earning more money. 800

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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120
Q

having more friends and relatives is much more likely to put a smile on your face than having more cash.27 804

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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121
Q

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). 807

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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122
Q

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. 810

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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123
Q

having more friends is not enough—having more happy friends is the key to our own emotional well-being. 814

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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124
Q

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. 817

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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125
Q

the more friends your friends have (regardless of their emotional state), the more likely you are to be happy. 819

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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126
Q

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. 823

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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127
Q

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. 829

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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128
Q

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. 832

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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129
Q

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. 834

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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130
Q

each of us tends to stay put in a particular long-term disposition; we appear to have a set point for personal happiness that is not easy to change. 860

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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131
Q

personal happiness appears to be strongly influenced by our genes. 862

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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132
Q

Behavior geneticists have used these studies to estimate just how much genes matter, and their best guess is that long-term happiness depends 50 percent on a person’s genetic set point, 10 percent on their circumstances (e.g., where they live, how rich they are, how healthy they are), and 40 percent on what they choose to think and do.31 863

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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133
Q

In some sense, loneliness is the opposite of connection—it is the feeling of being disconnected. 874

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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134
Q

psychologist John Cacioppo has shown that loneliness is a complex set of feelings experienced by people whose core needs for intimacy and social connection are not met.32 875

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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135
Q

Psychological research suggests that feelings of loneliness occur when there is a discrepancy between our desire for connection to others and the actual connections we have. 879

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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136
Q

People with more friends are less likely to experience loneliness. Each extra friend reduces by about two days the number of days we feel lonely each year. 885

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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137
Q

on average (in our data) people feel lonely forty-eight days per year, having a couple of extra friends makes you about 10 percent less lonely than other people. Interestingly, the number of family members has no effect at all. 886

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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138
Q

feelings of loneliness are much more closely tied to our networks of optional social connections than to those handed to us at birth. 890

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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139
Q

People who feel lonely all the time will lose about 8 percent of their friends, on average, over two to four years. Lonely people tend to attract fewer friends, 892

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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140
Q

loneliness is both a cause and a consequence of becoming disconnected. 893

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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141
Q

loneliness spreads three degrees, just like happiness. 905

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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142
Q

you are about 52 percent more likely to be lonely if a person you are directly connected to (at one degree of separation) is lonely. The effect for people at two degrees of separation is 25 percent, and for people at three degrees of separation, it is about 15 percent. At four degrees of separation the effect disappears, in keeping with the Three Degrees of Influence Rule. 907

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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143
Q

If we are concerned about combating the feeling of loneliness in our society, we should aggressively target the people at the periphery with interventions to repair their social networks. By helping them, we can create a protective barrier against loneliness that will keep the whole network from unraveling. 913

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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144
Q

there is one emotion central to human experience that we have not yet considered and that is key to understanding social connection: love. 922

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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145
Q

anthropologist Helen Fisher has argued, the sensibility of being in love may be broken down into lust, love, and attachment, all of which likely served evolutionary purposes.34 924

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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146
Q

we lose sight of the extraordinary degree to which our choice of a partner is determined by our surroundings and, in particular, by our social network. 978

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

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147
Q

Roughly 68 percent of the people in the study met their spouses after being introduced by someone they knew, while only 32 percent met via “self-introduction.” 991

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

148
Q

Even for short-term sexual partners like one-night stands, 53 percent were introduced by someone else. 992

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

149
Q

people ask family members for introductions to possible marriage partners and rely on their own resources to meet short-term partners. 1001

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

150
Q

from 1914 until 1960, 15 to 20 percent of people reported meeting their future spouses in the neighborhood, but by 1984 this percentage was down to 3 percent, reflecting the decline of geographically based social ties 1035

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

151
Q

Gone are the days of the girl next door. People increasingly meet their partners through (offline and online) social networks that are much less constrained by geography than they used to be. 1045

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

152
Q

the best way to search your network is to look beyond your direct connections but not so far away that you no longer have anything in common with your contacts. 1054

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

153
Q

homogamy, or the tendency of like to marry like (just as homophily is the tendency of like to befriend like). 1068

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

154
Q

72 percent of marriages exhibit homophily (based on a summary measure involving several traits), compared to 53 to 60 percent for other types of sexual relationships.10 1074

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

155
Q

people often care more about their relative standing in the world than their absolute standing. 1098

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

156
Q

economist John Kenneth Galbraith argued in 1958, many consumer demands arise not from innate needs but from social pressures.11 1099

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

157
Q

People assess how well they are doing not so much by how much money they make or how much stuff they consume but, rather, by how much they make and consume compared to other people they know. 1100

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

158
Q

are comparing themselves to those from whom they are three degrees removed. They do not compare themselves to strangers. Instead, they seem intent on impressing people they know. 1102

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

159
Q

people reported that they would rather work at a company where their salary was $33,000 but everyone else earned $30,000 than at another, otherwise identical company where their salary was $35,000 but everyone else earned $38,000.12 1103

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

160
Q

We would rather be big fish in a small pond than bigger fish in an ocean filled with whales. 1106

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

161
Q

A: Your physical attractiveness is 6; others average 4. B: Your physical attractiveness is 8; others average 10. Overall, 75 percent of people preferred being in situation A than in situation B. 1109

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

162
Q

relative standing is important if it has what is known as an instrumental payoff: a more appealing physique than others is a means to an end. 1116

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

163
Q

“I don’t need to outrun the bear; I just need to outrun you.” 1121

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

164
Q

the networks in which we are embedded function as reference groups, which is a social scientist’s way of saying “pond.” 1137

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

165
Q

comparative effects (how we or others evaluate ourselves), influence effects (the way others dictate our behaviors and attitudes), or both.15 1139

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

166
Q

Having unattractive social contacts may make us feel superior (comparison) but may also make us take worse care of ourselves (influence). These two effects may work at cross-purposes in our quest to find a partner. 1140

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

167
Q

There is thus a kind of unconscious social contagion in perceptions of attractiveness from one woman to another. 1163

A

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168
Q

Daniel Gilbert has shown that a woman can do a better job of predicting how much she will enjoy a date with a man by asking the previous woman who dated him what he is like than by knowing all about the man.20 1168

A

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169
Q

College-age women were more likely to rate a man as attractive if shown a photograph of him surrounded by four women than if shown a photograph of him alone. But college-age men were less likely to rate a woman as attractive if she was shown surrounded by four men than if she was shown alone. 1177

A

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170
Q

sociologists Peter Bearman, Richard Udry, Barbara Entwisle, and Kathleen Harris, designed and launched an ongoing, nationwide social-network study of American adolescents in 1994. Known as the Add Health study, 1190

A

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171
Q

girls with a close relationship with their fathers were less likely to become sexually active.22 1201

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172
Q

the number of friends, the age and gender of those friends, and their academic performance all affect the onset of sexual activity.23 1202

A

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173
Q

In a small number of “open” schools, where most opposite-sex friendships and romantic ties occur with individuals outside the school, more pledgers indeed meant delayed sexual debut. Surprisingly, though, in “closed” schools, where most ties occur inside the school, more pledgers meant a greater likelihood of sexual debut. These findings suggest that the pledge movement is an identity movement and not solely about abstaining from sex. 1211

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174
Q

if pledging becomes the norm, the psychological benefits of a unique identity are diminished, and the effect is lost. 1215

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175
Q

It’s not just the pledge itself that constrains behavior; it’s whether the pledge confers a unique status. 1216

A

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176
Q

Adolescents who believe that their peers would look favorably on being sexually active are more likely to have casual, nonromantic sex.26 1219

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177
Q

decisions about how many children to have and whether to use contraception spread across social ties.30 1229

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178
Q

the health benefits of marriage, and, conversely, the adverse health consequences of never marrying or of becoming widowed. As Farr 1260

A

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179
Q

married people seemed healthier due to a selection bias. Unhealthy people were less likely to get married, and healthy people were more likely to get married. 1275

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180
Q

which came first, health or marriage? Nineteenth-century observers could not tell. Scientific confusion persisted for a hundred years until the 1960s, 1282

A

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181
Q

mortality rate was 40 percent higher than expected for the first six months after a spouse’s death and then returned to the expected rate shortly thereafter. 1287

A

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182
Q

evidence that the risk of heart attack rises immediately after the death of a spouse.35 Something about being connected to a spouse affects our bodies and our minds. 1307

A

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183
Q

three explanations—homogamy, confounding, and a true causal effect—are 1309

A

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184
Q

being married adds seven years to a man’s life and two years to a woman’s life—better benefits than most medical treatments.36 1318

A

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185
Q

The emotional support spouses provide has numerous biological and psychological benefits. Being near a familiar person—even 1324

A

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186
Q

Spouses provide social support to each other and connect each other to the broader social network of friends, neighbors, and relatives. 1326

A

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187
Q

the main way marriage is helpful to the health of men is by providing them with social support and connection, via their wives, to the broader social world. Equally important, married men abandon what have been called “stupid bachelor tricks.”40 1333

A

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188
Q

process of social control, with wives modifying their husbands’ health behaviors, appears to be crucial to how men’s health improves with marriage. 1337

A

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189
Q

Conversely, the main way that marriage improves the health and longevity of women is much simpler: married women are richer. 1338

A

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190
Q

that perhaps this is just the age-old story of “trading sex for money”: women give men intimacy and a sense of belonging, and men give women cash. 1340

A

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191
Q

When men get married, they experience a sharp and substantial decline in their risk of death (the prompt elimination of stupid bachelor tricks). Women, on the other hand, do not derive an immediate health benefit. 1348

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

192
Q

When a wife dies, the husband’s risk of death rises abruptly and dramatically, so that men who lose their wives are between 30 percent and 100 percent more likely to die during the first year of widowhood. 1351

A

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193
Q

when men die, the thing they brought to the marriage that had the greatest impact on their spouse’s health, namely money, is still around—in the form of assets such as a house and a pension. Conversely, when women die, the thing they brought to a marriage that most affected their partner’s health, namely, emotional support, a connection to others, and a well-run home, disappears. 1361

A

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194
Q

Marriage to a younger woman is good for a man whereas marriage to a younger man is not good for a woman. 1372

A

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195
Q

the bigger the age difference (up to certain limits) between an older husband and a younger wife, the better for both parties when it comes to the health benefits of marriage.42 1373

A

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196
Q

white couples suffer a widowhood effect, but black couples do not. 1385

A

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197
Q

men married to black women did not experience a widowhood effect, whereas men married to white women did, regardless of the man’s own race.44 But how could a wife’s race affect her husband’s mortality during widowhood? 1389

A

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198
Q

the difference in marriage benefits between women and men is very likely to be a consequence of the greater ability of women to keep their spouses connected. 1397

A

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199
Q

The tendency to have several kinds of relationships (and sometimes many kinds of relationships with the same person) is called multiplexity. 1409

A

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200
Q

A person’s risk of illness depends not merely on his own behavior and actions but on the behavior and actions of others, some of whom may be quite distant in the network. 1477

A

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201
Q

They cannot meaningfully influence the overall shape of the network, even though it certainly influences them 1499

A

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202
Q

No one is interested in the battle for the bronze medal at the Olympics, and nobody wants to hook up with their ex-lover’s lover’s ex-lover. 1509

A

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203
Q

the more paths that connect you to other people in your network, the more susceptible you are to what flows within it. 1534

A

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204
Q

whites with many partners tend to have sex with other whites with many partners, and whites with few partners tend to have sex with whites with few partners. This keeps STDs in the core of active white partners. On the other hand, blacks with many partners have sex with other blacks with many and few partners. Hence, STDs spread more widely through the black population. 1545

A

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205
Q

safe-sex campaigns would be most effective if messages were directed at high-activity members (the cores, or hubs, of the networks) rather than targeted equally to all members of a community. 1551

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206
Q

focus on the architecture of a person’s social network, namely their structural position rather than their socioeconomic position. 1553

A

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207
Q

Studies of social networks are showing that people are placed at risk not so much because of who they are but because of who they know—that is, where they are in the network and what is going on around them. 1555

A

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208
Q

people randomly assigned to be seated near strangers who eat a lot wind up doing the same, and the effect can be so subconscious that it has been called “mindless eating.”13 It seems that we just can’t help imitating others. 1587

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209
Q

the word epidemic has two meanings. First, it means that there is a higher-than-usual prevalence of a condition. Second, it connotes contagion, suggesting that something is spreading rapidly. 1593

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210
Q

From 1990 to 2000, the percentage of obese people in the United States increased from 21 percent to 33 percent, and fully 66 percent of Americans are now overweight or obese. 1597

A

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211
Q

Framingham Heart Study that has been ongoing in Framingham, Massachusetts, just west of Boston, since 1948. 1605

A

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212
Q

Three Degrees of Influence Rule: the average obese person was more likely to have friends, friends of friends, and friends of friends of friends who were obese than would be expected due to chance alone. 1623

A

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213
Q

If a mutual friend becomes obese, it nearly triples a person’s risk of becoming obese. 1646

A

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214
Q

mutual friends are twice as influential as the friends people name who do not name them back. 1646

A

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215
Q

people are not influenced at all by others who name them as friends if they do not name them back. 1647

A

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216
Q

the obesity epidemic does not have a patient zero; it is not a unicentric epidemic but a multicentric epidemic. 1666

A

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217
Q

we now know that obesity is contagious. Since the publication of our study, we and three other independent teams have identified obesity contagion in other populations.15 1676

A

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218
Q

social critic Eric Hoffer once opined, “When people are free to do as they please, they usually imitate each other.” 1681

A

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219
Q

Behavioral imitation can be either conscious or subconscious. 1685

A

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220
Q

when we see someone eat or run, our mirror neurons fire in the same part of the brain that would be activated if we ourselves were eating or running. It is as if our brains practice doing something that we have merely been watching. 1685

A

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221
Q

It is deeply rooted in our biological capacity for empathy and even morality, and it is connected to our origins as a social species, 1690

A

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222
Q

What spreads from person to person is what social scientists call a norm, which is a shared expectation about what is appropriate.17 1694

A

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223
Q

there can be a concordance of norms even if there is not a concordance of behaviors. 1704

A

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224
Q

obesity can spread even between socially close people who are very far apart geographically. 1708

A

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225
Q

Norms can spread even if they do not affect a person’s behavior. Some people can be carriers of an idea without themselves exhibiting the behavior related to the idea. 1715

A

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226
Q

people detect and imitate local network norms about the acceptability of weight gain when our society as a whole still appears to privilege thinness? 1722

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

227
Q

People see images of ideal body types in the media, but they are less influenced by such images—by this ideology—than they are by the actions and the appearance of the very real people to whom they are actually connected. 1725

A

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228
Q

Ellen Goodman put it: “Professional anorexics such as Kate Moss, Calista Flockhart, and Victoria Beckham may present an incredibly shrinking ideal. But in real life we measure ourselves against our friends. Inch for inch.”18 1726

A

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229
Q

Over the past forty years, smoking among adults has decreased from 45 percent to 21 percent of the population. 1740

A

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230
Q

There is a kind of synchrony in time and space when it comes to smoking cessation that resembles the flocking of birds or schooling of fish. Whole interconnected groups of smokers, who may not even know one another, quit together at roughly the same time, as if a wave of opposition to smoking were spreading through the population. 1747

A

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231
Q

Decisions to quit smoking are not solely made by isolated individuals; rather, they reflect the choices made by groups of individuals connected to one another both directly and indirectly. 1750

A

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232
Q

as more and more people quit smoking over time, the smokers were forced to the periphery of their networks, just as they are now forced outdoors to smoke, even in the freezing cold. And it’s not just that they became less popular; they also tended to be friends with people who were less popular, which helped to speed up the dramatic increase in their social isolation. 1761

A

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233
Q

More connections within groups (in what is known as a concentrated network) can reinforce a behavior in the groups, but more connections between groups (in what is known as an integrated network) can open up a group to new behaviors and to behavioral change—for better or for worse. 1767

A

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234
Q

drinking appears to be greatly influenced by women. If a woman starts drinking heavily, both her male and her female friends are likely to follow suit. But when a man starts drinking more, he has much less effect on either his female friends or his male buddies down at the bar. 1778

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235
Q

Not all social ties are equal. 1789

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236
Q

friends affect each other more than spouses do in the spread of obesity. 1789

A

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237
Q

more susceptible to influence by peers of the same sex than by peers of the opposite sex. 1791

A

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238
Q

Harvard students were 8.3 percent more likely to get a flu shot if an additional 10 percent of their friends got a flu shot.22 1794

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

239
Q

The rate of lower back pain among working-age people is 10 percent in the United States, 36 percent in the United Kingdom, 62 percent in Germany, 45 percent in Denmark, and 22 percent in Hong Kong.24 1804

A

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240
Q

suggest that back pain can be seen as a culture-bound syndrome—a disease recognized in one society but not others, 1807

A

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241
Q

Koro, a condition that is seen in some Asian countries and that involves intense anxiety arising from the conviction among afflicted men that their penises are receding into their bodies and might disappear, and that they might die as a result. The treatment consists of asking trusted family members to hold the penis twenty-four hours a day for some number of days to prevent it from receding. 1809

A

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242
Q

one study of sororities, women who were binge eaters actually became more popular and moved to the center of the social network, 1823

A

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243
Q

Suicide contagion is perhaps the most devastating illustration of the power of social networks. 1827

A

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244
Q

suicide contagion occurs almost exclusively among the young. Adults older than twenty-four show little, if any, excess likelihood of killing themselves if someone they know has done so or if they simply read about a suicide in the paper.31 1873

A

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245
Q

Internet suicide clubs in Japan, the United Kingdom, the United States, and many other developed nations, which are formed by two or more strangers for the purpose of killing themselves together or simultaneously).34 1922

A

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246
Q

having a friend who committed suicide increased the likelihood of suicidal ideation. 1926

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

247
Q

1997 study found that 13 percent of American adolescents seriously considered suicide in the previous year, and 4 percent of adolescents actually attempted it.37 Moreover, 20 percent of adolescents reported having a friend who had attempted suicide in the previous year. From 1950 to 1990, the rate of successful suicide for people fifteen to twenty-four years of age increased from 4.5 to 13.5 per 100,000.38 1940

A

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248
Q

connections that can make us happy can also make us suicidal. 1947

A

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249
Q

people are more influenced by the people to whom they are directly tied than by imaginary connections to celebrities. 1978

A

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250
Q

identify the hubs in the social network (who might or might not be poor or smokers) and target them with smoking-cessation messages. Early results with such approaches have documented success in fostering better diets and safer sex.43 1983

A

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251
Q

In addition to focusing, for example, on whether people are poor or where they live, we might focus on who they know and what kinds of networks they inhabit. 1988

A

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252
Q

Computer models of the obesity epidemic confirm that targeting central individuals in the network to encourage healthy weight can be an effective strategy, whether these central people are overweight or not.45 1999

A

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253
Q

at both the individual and the population levels, it is more effective for you to lose weight with friends of friends than with friends. The problem is this: If you attempt to lose weight with your friends, you might succeed, but this tiny cluster of you and your friends is surrounded by a large group of people exerting pressure to gain weight again. In all likelihood, both you and your friends will thus regain weight. 2002

A

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254
Q

A choice informed by network science could be seven hundred times more effective and efficient.47 2018

A

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255
Q

Kelly and O’Grada found that social networks were the single most important factor in explaining the closure of accounts during both panics, even more so than the size of the accounts or the length of time they had been opened. Thus, financial panics may result from the spread of emotions or information from person to person. 2101

A

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256
Q

individually rational behavior can lead to communally irrational behavior. We are all capable of thinking with our heads, but our hearts keep in touch with the crowd, and sometimes this leads us to disaster. 2108

A

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257
Q

in 1998, a database consultant from Brookline, Massachusetts, named Hank Eskin figured out a way to satisfy this curiosity. He started a website called Where’s George? (WheresGeorge.com). 2122

A

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258
Q

As of 2008, more than 133 million bills had been tracked, with a total value of over $729 million (the site accepts all denominations). One user, Gary Wattsburg, has entered almost a million of those bills himself, but the majority of the bills are reported by newcomers to the website. 2129

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

259
Q

it took more than three years for the plague to move from the southern part of Europe to its northern reaches, with an average speed of movement of two or three miles a day.11 2159

A

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260
Q

one of the people involved in the 2003 SARS outbreak carried the infection eight thousand miles (from China to Canada) in a single day! 2161

A

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261
Q

The overall pattern indicates two important features of human interaction. First, bills stay much closer to home for a much longer time than previous models of human movement had predicted. Our regular routine involves straying little and spending cash locally. Yet, when bills do jump from one place to another, the distance they jump is typically much longer than previous models of human behavior had predicted. 2183

A

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262
Q

the jumps follow a mathematical pattern poetically called a Lévy flight, after the French mathematician Paul Pierre Lévy. 2186

A

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263
Q

The random walk (left) shows five thousand steps of equal length in a random pattern of movement. In contrast, the Lévy flight (right) shows five thousand steps of varying length, sometimes with a “flight,” in a random pattern of movement. 2193

A

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264
Q

markets tend to oscillate near a given price for a while and then jump to a new one. 2215

A

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265
Q

Human social networks thus have economic moods. 2238

A

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266
Q

The economic boom in the 1890s in Boston and New York gave rise to the decade’s moniker “the gay nineties,” and we use equally evocative expressions when we speak of economic downturns as “panics” and “depressions.” 2239

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

267
Q

“Vox Populi” (Latin for “voice of the people”), a 1907 article in Nature by polymath statistician Francis Galton.15 Galton visited the West of England Fat Stock and Poultry Exhibition, a county fair where there was a contest to guess the weight of a fattened ox. Participants had to pay six cents to guess, and the closest guesses won prizes. Galton managed to acquire the cards on which people had made their guesses, and he showed that most guesses were quite bad. However, when he ordered them from the lowest guess to the highest guess, he found that the median guess (1207 pounds) was extremely close to the actual weight of the ox (1198 pounds). Galton concluded, to his own surprise, that democratic decision making might not be as bad as previously thought. 2246

A

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268
Q

When faced with the challenge of identifying the correct weight of the ox, most individuals would get it wrong, but the group as a whole could get it right. 2252

A

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269
Q

compared market predictions with what actually happens, and they have shown that election markets predict outcomes better than other available methods, such as polling.16 2259

A

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270
Q

economists will point to markets like these to emphasize the triumph of the invisible hand, it is important to note that they are, in fact, special cases of group activities. In the fattened ox example, individual guesses were made independently. 2264

A

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271
Q

Whether groups of people are able to reach a correct decision about something (the value of a product, the number of jelly beans in a jar, the weight of an ox) depends on whether decisions are made at the same time or sequentially. 2274

A

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272
Q

present in this community than in others nearby. The people in Tigua Loma had a problem. They didn’t talk to one another. 2314

A

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273
Q

Strong ties may bind individuals together into groups, but weak ties bind groups together into the larger society 2347

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

274
Q

“Prior to switching employers, how often did you see the person who helped you get the new job?” He found that only 17 percent responded “often,” while 55 percent said “occasionally”; the remaining 28 percent said “rarely.” Most workers found jobs via old college friends, past workmates, or previous employers. 2351

A

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275
Q

most of his subjects had acquired their jobs by (nearly) relying on the kindness of strangers. These were distant friends or friends of friends who passed their names to an employer or who passed information about jobs to the prospective employee. 2357

A

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276
Q

We might trust socially distant people less, but the information and contacts they have may be intrinsically more valuable because we cannot access them ourselves. 2366

A

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277
Q

people who have many weak ties will be frequently sought out for advice or offered opportunities in exchange for their information or access. In other words, people who act as bridges between groups can become central to the overall network and so are more likely to be rewarded financially and otherwise. 2367

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

278
Q

Wealthy individuals and big businesses shape their networks according to their financial and economic goals, and in turn, the shape of their networks has a big impact on whether they can achieve those goals. The good ol’ boys circle together and take care of their own. 2379

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

279
Q

Although today corporations rarely seal deals through intermarriage, they do share executives on their boards of directors. 2398

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

280
Q

real-world interactions are often based on personal relationships between businesses that are embedded (strongly connected) in stable networks of trust and reciprocity. 2414

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

281
Q

too much embeddedness can be a bad thing. An unconditional commitment to a particular business partner (a strong tie) can be disastrous if it causes a firm to completely ignore opportunities with other firms (weak ties). Thus, there is a trade-off 2419

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

282
Q

building stable relationships with a certain group of partners and being willing to leave those relationships when changes in the market cause them to lose viability. It is important to have a mix of strong and weak ties, 2421

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

283
Q

small-world networks is that they exhibit two important features: low average path length (people can easily reach others in the network through a small number of intermediaries, as Stanley Milgram’s Nebraska mail experiment illustrated) and high transitivity (most of a person’s friends are friends with one another). 2431

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

284
Q

sweet spot that combines the diversity of new team members with the stability of previously formed relationships. 2440

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

285
Q

Breakthroughs are created in collaborative circles, and networks can amplify talent 2448

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

286
Q

Using citation as a measure of quality, Uzzi found that, on average, team efforts were judged to be better and more important science than efforts by individuals. 2454

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

287
Q

“thirty-foot rule.” This rule states that people collaborate only with others within thirty feet of them. 2456

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

288
Q

physical distance is becoming less of a constraint on scientific collaboration. 2459

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

289
Q

small differences in the overall patterns of connection in the network can matter a great deal to the performance of the group. 2481

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

290
Q

those with the most neighbors were able to drive the entire network to their preferred color. The investigators called this the minority-power effect. A small group of influentially positioned individuals can consistently get their way. 2498

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

291
Q

although social networks may help us do what we could not do on our own, they also often give more power to people who are well connected. 2501

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

292
Q

those with the most connections often reap the highest rewards. 2502

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

293
Q

Social networks help distribute risk and help groups cope more effectively with unexpected events 2526

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

294
Q

Yunus: “A sense of intergroup and intragroup competition also encourages each member to be an achiever.”33 2535

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

295
Q

women are much more likely than men to invest in improving the lives of children via schooling and improved health services. Women are also more likely to invest in their husbands than men are in their wives. 2538

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

296
Q

Obama succeeded because these “working men and women” felt connected. 2575

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

297
Q

Many have commented on Obama’s remarkable ability to connect with voters, but even more impressive was his ability to connect voters to each other. 2577

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

298
Q

Dean’s campaign raised a lot of money but failed to mobilize supporters because they were not yet connected to one another. 2583

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

299
Q

Hughes built the social networking site My.BarackObama.com, which logged 1.5 million accounts at its peak. 2586

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

300
Q

Rationally speaking, each vote doesn’t count. The reason we vote, it turns out, has a lot to do with our embeddedness in groups and with the power of our social networks. 2603

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

301
Q

The closest was an election for the representative for New York’s 36th congressional district in 1910, when the Democratic candidate won by a single vote, 20,685 to 20,684. However, a subsequent recount in that election found a mathematical error that greatly increased the margin, meaning there are actually no examples of single-vote wins. 2649

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

302
Q

How much would you hand over to be the kingmaker, the one person who chooses who runs the country for the next four years? One dollar? Ten dollars? One million dollars? When undergraduates answer this question, they usually give amounts of less than $10, 2665

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

303
Q

A large body of evidence suggests that a single decision to vote in fact increases the likelihood that others will vote. 2705

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

304
Q

when you decide to vote it also increases the chance that your friends, family, and coworkers will vote.10 2706

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

305
Q

social connections may be the key to solving the voting puzzle. 2710

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

306
Q

the media does not reach the masses directly. Instead, a group of “opinion leaders” usually acts as an intermediary, filtering and interpreting the media for their friends and family who pay less attention to politics. 2731

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

307
Q

Several election studies show that we typically talk to only a few people about politics; in one study in which people were asked to name their “discussion partners,” about 70 percent reported fewer than five (on any topic).14 2753

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

308
Q

if you vote, then it increases the likelihood that your friends’ friends vote as well. 2767

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

309
Q

If you knew you could get lots of people to support your favorite candidate just by voting, you would probably be more likely to do it than if you thought your vote would get canceled out by a mix of people from the Left and Right. 2781

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

310
Q

in ideologically polarized environments, the incentive to vote might be magnified by the number of like-minded individuals you could motivate to go to the polls. 2782

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

311
Q

the total number of people voting had virtually no effect on how far the cascades would spread in our computer model. 2795

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

312
Q

we discovered that turnout cascades are primarily local phenomena, occurring in small parts of the population within a few degrees of separation from each individual. 2797

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

313
Q

the power of one individual to influence many is limited by the effect of competing waves of influence that emanate from everyone else in the network. 2798

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

314
Q

Putnam argues that highly clustered network ties improve information flow and increase reciprocity at a societal level because everyone is looking out for everyone else. In other words, more tightly knit connections are better for society. However, our work shows that, at a certain point, networks can become so transitive that norms and information simply circulate within groups rather than traveling between them. 2816

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

315
Q

democratic citizens work best in “small worlds” where some of our friends know one another and others do not. 2820

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

316
Q

The big surprise, however, was in the behavior of the people who did not answer the door. As it turns out, the other person in the household was about 6 percent more likely to vote. In other words, 60 percent of the effect on the person who answered the door was passed on to the person who did not answer the door. 2829

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

317
Q

many of our friends already know one another, which means the effect might bounce around between the same people and never reach others who are socially distant from us. 2846

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

318
Q

Instead of each of us having only one vote, we effectively have several and are therefore much more likely to have an influence on the outcome of an election. 2851

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

319
Q

Typically, about 20 to 30 percent of the people who say they voted in an election actually did not. 2860

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

320
Q

politicians tend to manipulate their networks for political advantage. 2885

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

321
Q

bills with many cosponsors (sometimes called “Mom and Apple Pie” bills by political scientists) are frequently supported by legislators who had no contact with the sponsor. 2961

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

322
Q

the best-connected representatives were able to garner ten more votes than average (out of 435 representatives), while the best-connected senators were able to garner sixteen more (out of 100 senators). 3004

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

323
Q

if a bill is introduced by a person in the middle of the network, it would pass; but if the same bill were introduced by someone just outside of the middle, it would fail. Connectedness matters. 3007

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

324
Q

But Keith was in greater danger of being voted out of the competition, and so he said to Tina, “I need this one,” and she willingly dropped into the water. 3165

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

325
Q

I knew that for the good of our team, I had to let Keith win.” 3167

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

326
Q

Colby had chosen friendship over what seemed like certain victory. 3174

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

327
Q

Many people questioned Colby’s decision and claimed that he had miscalculated. But another plausible interpretation is that friendship and loyalty had trumped self-interest. 3176

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

328
Q

Like ants, bees, penguins, wolves, dolphins, and chimpanzees, human beings are social animals, living in close proximity to one another in groups. 3185

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

329
Q

Our embeddedness in social networks means that we must cooperate with others, judge their intentions, and influence or be influenced by them. 3190

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

330
Q

humans don’t just live in groups, we live in networks. 3192

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

331
Q

some species exhibit bucket-brigade behavior because it is an efficient adaptation to their environment; consider ants that pass food items from one worker to another, for example.2 3204

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

332
Q

Among early hominids, individuals who lived in social networks that enabled a group to acquire more food or to fend off attackers were more likely to survive and reproduce. As a result, over a long period of time, the individuals who naturally formed networks or who had specific traits conducive to forming particular kinds of networks would have had a selective advantage and might eventually have made up the largest part of the population. 3229

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

333
Q

This is the puzzle of cooperation and altruism: people who are willing to help others should be, it might seem, less likely to survive than people who care only about themselves. 3239

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

334
Q

cooperators who are willing to pay a personal cost to help a group of people are less likely to survive than free riders who do not pay a personal cost but benefit from the group’s activities. 3240

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

335
Q

when humans learned to hunt large game hundreds of thousands of years ago, this gave a fitness advantage to the groups that knew how to do it. But if it is risky to take down a mastodon, why not let someone else do it? If you are the most selfish person in your group, then presumably you would be more likely to survive. 3242

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

336
Q

Ian McEwan, in Enduring Love, provides a vivid illustration of the problem of cooperation. A helium balloon is hovering near the ground in a green English field in strong winds. Curled up inside the basket is a frightened boy, and outside, hanging to a rope, is his grandfather, desperately trying to control the balloon before it is blown away. 3245

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

337
Q

“enacted morality’s ancient, irresolvable dilemma: us, or me.”3 3254

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

338
Q

The good news is that people very often ignore their selfish tendencies when interacting with people to whom they are connected. 3255

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

339
Q

evolutionary theory to whether it makes sense to help other people would be incorrect. Selfishness does not always pay. If it did, we would all be selfish. 3259

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

340
Q

Tina might have given up because she knew she would be competing with Keith in future challenges and would need his help. Evolutionary theorists call this direct reciprocity. If you have several opportunities to cooperate with the same person, one way to get that person to help you is to promise future cooperation. 3261

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

341
Q

scientist Robert Axelrod showed that a cooperative strategy called “tit for tat” often is more effective than always cooperating or always being selfish.4 3264

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

342
Q

the first time you meet a selfish person you will cooperate with him but he won’t cooperate with you. You learned your lesson, and you will copy him in any future interaction, but that first meeting means he is a little more likely to do better since he got something from you on the very first interaction. 3270

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

343
Q

what if they could choose not to interact? Rather than attempting to cooperate and risking being taken advantage of, a person could fend for herself. In other words, she could sever her connections to others in the network. Hauert called the people who adopt this strategy “loners.” 3276

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

344
Q

in a world full of loners it is easy for cooperation to evolve because there are no people to take advantage of the cooperators that appear. 3279

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

345
Q

The loners fend for themselves, and the cooperators form networks with other cooperators. Soon, the cooperators take over the population because they always do better together than the loners. 3280

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

346
Q

But once the world is full of cooperators, it is very easy for free riders to evolve and enjoy the fruits of cooperation without contributing 3281

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

347
Q

cooperation can emerge because we can do more together than we can apart. But because of the free-rider problem, cooperation is not guaranteed to succeed. 3284

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

348
Q

To deal with free riders, another type of person is needed: punishers. People everywhere feel the desire to enforce social norms they see being violated. 3285

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

349
Q

Cooperators connect to others in order to create more; free riders connect in order to leach off those who create; and punishers connect in order to drive away free riders. 3289

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

350
Q

showed that small groups of interconnected, interacting cooperators and punishers could coevolve in a world of people who otherwise keep to themselves, and this pushes the whole population toward higher overall levels of cooperation and connection.7 3294

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

351
Q

the population was frequently in transition, meaning that we might expect to find different proportions of individuals of different types at any given moment. 3298

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

352
Q

the model predicted two things: some people will cooperate, and others will not; and some people will be well connected to the social network, and others—the loners—will not. 3301

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

353
Q

The standard way of thinking about human beings in economics is that every person makes a decision without considering the interests of others (except insofar as the interests of others impinge on one’s own). 3304

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

354
Q

incentive compatible: I scratch your back because I think you are going to scratch mine. 3306

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

355
Q

The expression Homo economicus, a slightly tongue-in-cheek construction, was first used at least one hundred years ago to describe a vision of our species as one that relies on self-interest to obtain the maximum personal good at the lowest possible cost. 3310

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

356
Q

in 1836, philosopher John Stuart Mill was already propounding a model of “economic man” who “inevitably does that by which he may obtain the greatest amount of necessaries, conveniences, and luxuries, with the smallest quantity of labour and physical self-denial with which they can be obtained.”9 3312

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

357
Q

Implicit in this vision is that people are lazy and greedy but also rational and self-interested and self-directed. Such a model leaves no room for altruism. 3314

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

358
Q

Homo dictyous (from the Latin homo for “human” and the Greek dicty for “net”), or “network man,” 3317

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

359
Q

This perspective allows our motivations to depart from pure self-interest. Because we are connected to others, and because we have evolved to care about others, we take the well-being of others into account when we make choices about what to do. Moreover, by stressing our embeddedness, this perspective allows us to formally include in our understanding of people’s desires a critical source: the desires of those around them. 3318

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

360
Q

some of our tastes may be for things that are made more desirable when others desire them. 3325

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

361
Q

In 1982, a group of economists developed a simple but clever experiment called the “ultimatum game” in which two players bargain over $10 given to them by the experimenter.10 3331

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

362
Q

economists found that subjects frequently rejected low offers. Offers of $2 were rejected about half the time, and lower offers were rejected even more frequently. 3340

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

363
Q

The most common offer was an exact fifty-fifty split, and, on average, the first player earned a little bit more than the second player, but not much more because rejected offers caused both players to lose everything. 3342

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

364
Q

a new so-called dictator game 3348

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

365
Q

In this game, the first player is given $10 and allowed to divide it between herself and the second player any way she likes. But now the second player can do nothing. 3348

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

366
Q

economists expected that the first player would keep everything, and many did. But many more did not. The average first player gave away about $2 to the second player. The results of this extremely simple experiment were difficult to explain if we thought of behavior as being driven purely by self-interest. People were literally taking money out of their own pockets and giving it to anonymous strangers. 3350

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler

367
Q

Some people care only about themselves. But the majority of us take other peoples’ well-being and interests into account. 3357

A

Connected: The Surprising Power of Our Social Networks by Nicholas A. Christakis, James H. Fowler